#ApplyTime
از زمانی که کانال #اپلای تایم راهاندازی شده است، اندکی بیش از 3 سال میگذرد! شاید باور کردنش دشوار باشد، ولی در طول این 3 سال بیش از 5000 موقعیت و یا بورسیهی تحصیلی در مقاطع گوناگون، رشتههای متنوع، و کشورهای مختلف با شما به اشتراک گذارده شده است! جدا از پستهای دیگری که در برگیرندهی فایلهای آموزشی یا راهنماییهایی جهت طی مسیر اپلای بودند. و سوا از ارائهی مشاورهی رایگان به بیش از 3000 نفر فقط از طریق تلگرام!!!
چه بسیار دوستانی که برای آن پوزیشنها اپلای کردند، و چه بسیار کسانی که در نهایت پاسخ مثبت دریافت کردهاند. مبارکشان باشد! :)
در ادامهی روند تصمیم گرفتیم که با ایجاد یک گروه تلگرامی برای کانال پوزیشنها، مشارکت عزیزانی که علاقهمند هستند به دیگران کمک کنند را نیز جلب کنیم. بسیاری از ما احتمالا در طول روز با موقعیتها یا بورسیههای تحصیلیای برخورد میکنیم که برخی از آنها برای خود ما مناسب نیست، ولی شاید برای دیگر هموطنانمان مفید باشد. در نتیجه چه خوب است که لینک آنها را با دیگران به اشتراک بگذاریم! اگر اپلای تایم به تنهای توانسته بیش از 5000 پوزیشن را به اشتراک بگذارد، چنانچه همهی ما با هم همکاری کنیم، چند پوزیشن میشود به اشتراک گذاشت؟!؟
شما میتوانید با مراجعه به گروه زیر، لینک این گونه موقعیتها یا بورسیههای تحصیلی را با دیگران به اشتراک بگذارید:
https://news.1rj.ru/str/applytime_academic_positions
قوانین مربوط به اشتراک گذاری لینکها در خود گروه توضیح داده شده است. اما به اختصار لازم به توضیح است، که این گروه برای تبادل نظر در زمینهی اپلای طراحی نشده است، بلکه تنها و تنها جهت به اشتراک گذاری موقعیتها یا بورسیههای تحصیلی میباشد.
اپلای تایم نیز مانند گذشته پوزیشنهایی را از طریق کانال یا وبسایت به اشتراک خواهد گذاشت.
از زمانی که کانال #اپلای تایم راهاندازی شده است، اندکی بیش از 3 سال میگذرد! شاید باور کردنش دشوار باشد، ولی در طول این 3 سال بیش از 5000 موقعیت و یا بورسیهی تحصیلی در مقاطع گوناگون، رشتههای متنوع، و کشورهای مختلف با شما به اشتراک گذارده شده است! جدا از پستهای دیگری که در برگیرندهی فایلهای آموزشی یا راهنماییهایی جهت طی مسیر اپلای بودند. و سوا از ارائهی مشاورهی رایگان به بیش از 3000 نفر فقط از طریق تلگرام!!!
چه بسیار دوستانی که برای آن پوزیشنها اپلای کردند، و چه بسیار کسانی که در نهایت پاسخ مثبت دریافت کردهاند. مبارکشان باشد! :)
در ادامهی روند تصمیم گرفتیم که با ایجاد یک گروه تلگرامی برای کانال پوزیشنها، مشارکت عزیزانی که علاقهمند هستند به دیگران کمک کنند را نیز جلب کنیم. بسیاری از ما احتمالا در طول روز با موقعیتها یا بورسیههای تحصیلیای برخورد میکنیم که برخی از آنها برای خود ما مناسب نیست، ولی شاید برای دیگر هموطنانمان مفید باشد. در نتیجه چه خوب است که لینک آنها را با دیگران به اشتراک بگذاریم! اگر اپلای تایم به تنهای توانسته بیش از 5000 پوزیشن را به اشتراک بگذارد، چنانچه همهی ما با هم همکاری کنیم، چند پوزیشن میشود به اشتراک گذاشت؟!؟
شما میتوانید با مراجعه به گروه زیر، لینک این گونه موقعیتها یا بورسیههای تحصیلی را با دیگران به اشتراک بگذارید:
https://news.1rj.ru/str/applytime_academic_positions
قوانین مربوط به اشتراک گذاری لینکها در خود گروه توضیح داده شده است. اما به اختصار لازم به توضیح است، که این گروه برای تبادل نظر در زمینهی اپلای طراحی نشده است، بلکه تنها و تنها جهت به اشتراک گذاری موقعیتها یا بورسیههای تحصیلی میباشد.
اپلای تایم نیز مانند گذشته پوزیشنهایی را از طریق کانال یا وبسایت به اشتراک خواهد گذاشت.
New Post-doc Opening at U. of Toronto on Deep Learning / RL for Traffic Prediction and Control
Salary for the position is highly competitive. An initial offer would be made for one year with possibility of renewal for one or more years. Post-docs are expected to publish in the top venues relevant to the project research area and to produce high-quality deliverable code for use by research funding partners.
If you are interested, please email ssanner@mie.utoronto.ca with the following:
(a) your CV (clearly listing all publications),
(b) your github, gitlab, or bitbucket public account link with deep learning / reinforcement learning coding projects that we can browse,
(c) 1-2 sentences in your email stating why the position interests you and why you think you are appropriate for the position.
We are seeking to fill this new opening as soon as possible.
Dr. Scott P. Sanner
Assistant Professor, Industrial Engineering
Cross-appointed, Computer Science
Faculty Affiliate, Vector Institute
University of Toronto, Toronto, ON, Canada
Email: ssanner@mie.utoronto.ca
Website: http://d3m.mie.utoronto.ca
✔️ @ApplyTime
Salary for the position is highly competitive. An initial offer would be made for one year with possibility of renewal for one or more years. Post-docs are expected to publish in the top venues relevant to the project research area and to produce high-quality deliverable code for use by research funding partners.
If you are interested, please email ssanner@mie.utoronto.ca with the following:
(a) your CV (clearly listing all publications),
(b) your github, gitlab, or bitbucket public account link with deep learning / reinforcement learning coding projects that we can browse,
(c) 1-2 sentences in your email stating why the position interests you and why you think you are appropriate for the position.
We are seeking to fill this new opening as soon as possible.
Dr. Scott P. Sanner
Assistant Professor, Industrial Engineering
Cross-appointed, Computer Science
Faculty Affiliate, Vector Institute
University of Toronto, Toronto, ON, Canada
Email: ssanner@mie.utoronto.ca
Website: http://d3m.mie.utoronto.ca
✔️ @ApplyTime
MERL is seeking a motivated and qualified individual to conduct research in safe reinforcement learning (RL) and deep learning algorithms for robotics applications. The ideal candidate should have solid background in RL (PhD level). Knowledge of deep learning algorithms is a plus. Publication of the results produced during the internship is anticipated. Duration of the internship is expected to be 3 months. Start date is flexible.
Contact: Dr. M. Benosman
Link: https://www.merl.com/internship/openings.php?tags=benosman
✔️ @ApplyTime
Contact: Dr. M. Benosman
Link: https://www.merl.com/internship/openings.php?tags=benosman
✔️ @ApplyTime
Merl
Internship Openings
Mitsubishi Electric Research Laboratories (MERL) - Internship Openings
Hi, everyone. We're now accepting applications for summer 2020 Research Interns at the following link: https://smrtr.io/3D3zr. See my previous email below for information on our group, located in the AI Lab of UT Austin.
For the Research Scientist and Research Engineer positions linked to below, we expect to only consider applications submitted by the end of this week.
Best regards,
Brad
____________________
W. Bradley Knox, PhD
✔️ @ApplyTime
For the Research Scientist and Research Engineer positions linked to below, we expect to only consider applications submitted by the end of this week.
Best regards,
Brad
____________________
W. Bradley Knox, PhD
✔️ @ApplyTime
Telegram
Academic Positions
MERL is seeking a motivated and qualified individual to conduct research in safe reinforcement learning (RL) and deep learning algorithms for robotics applications. The ideal candidate should have solid background in RL (PhD level). Knowledge of deep learning…
7 Postdoctoral Research Positions - ML & AI for Healthcare
Computational Health Informatics (CHI) Laboratory,
Department of Engineering Science, University of Oxford
The CHI Lab, led by David Clifton (Oxford Professor of Clinical Machine Learning), has sites in Oxford (funded by the Wellcome Trust, UK government, and NHS) and Suzhou, China (funded by the Chinese government), with over 30 researchers. We develop (non-imaging) interventions for use in healthcare that are based on machine learning, typically involving time-series analysis, Bayesian nonparametrics, and generative deep learning. In close collaboration with Oxford University Hospitals, we have acquired some of the world’s largest sets of patient data (> 1M admissions). We collaborate closely with industry to deploy our methods across hospitals at scale - our work is typically patented by Oxford University Innovation, for immediate translation into healthcare practice. Recent outcomes include the public listing on the UK stock exchange of a company (now approaching 100 employees) to implement our research, alongside other spin-outs.
CHI Lab has openings for postdoctoral researcher scientists, in ML & AI for healthcare, across three sites:
· Four postdocs across a variety of novel Oxford-based clinical collaborations; https://bit.ly/387NZAI
· One postdoc in our Chinese lab in Suzhou; https://bit.ly/2OQsVYa
· Two senior postdocs in our new Wellcome Trust-funded “Flagship Centre”, based in Ho Chi Minh City, Vietnam, sited within the Oxford University Clinical Research Unit (containing 300 Oxford researchers). This initiative focuses on developing novel hospital-based AI interventions suitable for resource-constrained settings, and the posts include a generous package of “overseas allowances”. https://bit.ly/2DGQ5d4
Our lab’s members come from a variety of backgrounds, including machine learning, signal processing, imaging, statistics, and clinical medicine. You will have the opportunity to develop novel technologies based on machine learning as part of a highly collaborative team, with coinventorship on patents, publication in the engineering and medical literature (with leading clinical collaborators), and potential involvement with spin-out and industrial activity according to your interests.
Please contact Prof. David Clifton for informal enquiries: davidc@robots.ox.ac.uk
✔️ @ApplyTime
Computational Health Informatics (CHI) Laboratory,
Department of Engineering Science, University of Oxford
The CHI Lab, led by David Clifton (Oxford Professor of Clinical Machine Learning), has sites in Oxford (funded by the Wellcome Trust, UK government, and NHS) and Suzhou, China (funded by the Chinese government), with over 30 researchers. We develop (non-imaging) interventions for use in healthcare that are based on machine learning, typically involving time-series analysis, Bayesian nonparametrics, and generative deep learning. In close collaboration with Oxford University Hospitals, we have acquired some of the world’s largest sets of patient data (> 1M admissions). We collaborate closely with industry to deploy our methods across hospitals at scale - our work is typically patented by Oxford University Innovation, for immediate translation into healthcare practice. Recent outcomes include the public listing on the UK stock exchange of a company (now approaching 100 employees) to implement our research, alongside other spin-outs.
CHI Lab has openings for postdoctoral researcher scientists, in ML & AI for healthcare, across three sites:
· Four postdocs across a variety of novel Oxford-based clinical collaborations; https://bit.ly/387NZAI
· One postdoc in our Chinese lab in Suzhou; https://bit.ly/2OQsVYa
· Two senior postdocs in our new Wellcome Trust-funded “Flagship Centre”, based in Ho Chi Minh City, Vietnam, sited within the Oxford University Clinical Research Unit (containing 300 Oxford researchers). This initiative focuses on developing novel hospital-based AI interventions suitable for resource-constrained settings, and the posts include a generous package of “overseas allowances”. https://bit.ly/2DGQ5d4
Our lab’s members come from a variety of backgrounds, including machine learning, signal processing, imaging, statistics, and clinical medicine. You will have the opportunity to develop novel technologies based on machine learning as part of a highly collaborative team, with coinventorship on patents, publication in the engineering and medical literature (with leading clinical collaborators), and potential involvement with spin-out and industrial activity according to your interests.
Please contact Prof. David Clifton for informal enquiries: davidc@robots.ox.ac.uk
✔️ @ApplyTime
Fully-funded Post Doctoral Position at InterDigitl, Information Theory for Understanding and Designing Flexible Deep Neural Networks
Running deep neural networks (DNNs) at the Edge and in consumer electronic (CE) devices remains still very challenging due to limited computational and memory resources. Moreover, usually those resources are constantly varying due to other concurrent processes that may start or stop. To optimally use varying resources, one needs so-called flexible DNN models, i.e., models that can optimally exploit all resources available at a given time.
We are targeting the design of such flexible models as follows. A flexible DNN is a network containing several simplified sub-networks of different complexities. This should allow optimally exploiting all available computational resources by executing an appropriate sub-network. However, designing such networks is difficult and time consuming. More precisely, designing an architecture of a usual (non-flexible) DNN is already time consuming, since one needs trying various numbers of layers, various numbers of neurons in each layer, etc. In case of flexible models we are targeting, one needs designing architectures of all sub-networks, which drastically increases the number of tries needed.
In this work we propose to look at the DNNs under the angle of information theory. Indeed, several recent works proposed to study DNNs [1, 2, 3, 4] using the information bottleneck principle [5]. This principle allows obtaining some theoretical bounds of DNN performance by quantifying mutual information between its layers. This will allow finding some near-optimal network simplification rules (going from one sub-network to another) based on theoretical findings, thus avoiding exhaustive cumbersome design of each sub-network. Moreover, we hope that this theoretical work will lead to other new results and findings.
Qualifications
PhD, in Computer Science, Signal Processing, Machine Learning, Mathematics.
Strong analytical and problem-solving skills
Excellent Mathematical / Statistical Skills, Machine Learning and Deep Learning
Strong knowledge in Information Theory
Good programming skills and / or simulation tools. SW (C/C++/Python)
Ability to conduct independent research, propose patents and publications
Ability to conduct independent research
Excellent communication skills and ability to work in a team
ML/AI scientist with a strong expertise and relevant background in distributing model for both inference and training.
Fluent in English
Location: Rennes, France
To apply:
Please send your cv and cover letter to Alexey Ozerov Alexey.Ozerov@InterDigital.com
✔️ @ApplyTime
Running deep neural networks (DNNs) at the Edge and in consumer electronic (CE) devices remains still very challenging due to limited computational and memory resources. Moreover, usually those resources are constantly varying due to other concurrent processes that may start or stop. To optimally use varying resources, one needs so-called flexible DNN models, i.e., models that can optimally exploit all resources available at a given time.
We are targeting the design of such flexible models as follows. A flexible DNN is a network containing several simplified sub-networks of different complexities. This should allow optimally exploiting all available computational resources by executing an appropriate sub-network. However, designing such networks is difficult and time consuming. More precisely, designing an architecture of a usual (non-flexible) DNN is already time consuming, since one needs trying various numbers of layers, various numbers of neurons in each layer, etc. In case of flexible models we are targeting, one needs designing architectures of all sub-networks, which drastically increases the number of tries needed.
In this work we propose to look at the DNNs under the angle of information theory. Indeed, several recent works proposed to study DNNs [1, 2, 3, 4] using the information bottleneck principle [5]. This principle allows obtaining some theoretical bounds of DNN performance by quantifying mutual information between its layers. This will allow finding some near-optimal network simplification rules (going from one sub-network to another) based on theoretical findings, thus avoiding exhaustive cumbersome design of each sub-network. Moreover, we hope that this theoretical work will lead to other new results and findings.
Qualifications
PhD, in Computer Science, Signal Processing, Machine Learning, Mathematics.
Strong analytical and problem-solving skills
Excellent Mathematical / Statistical Skills, Machine Learning and Deep Learning
Strong knowledge in Information Theory
Good programming skills and / or simulation tools. SW (C/C++/Python)
Ability to conduct independent research, propose patents and publications
Ability to conduct independent research
Excellent communication skills and ability to work in a team
ML/AI scientist with a strong expertise and relevant background in distributing model for both inference and training.
Fluent in English
Location: Rennes, France
To apply:
Please send your cv and cover letter to Alexey Ozerov Alexey.Ozerov@InterDigital.com
✔️ @ApplyTime
Pre- or Post-Doc Position in Family Demography - DEADLINE 15 December
Masaryk University seeks to appoint a doctoral student or a post-doctoral scholar in the Office of Population Studies and Department of Sociology as soon as possible, but no later than July 1, 2020.
The appointment is for 2 years, FTE is negotiable (between 0.5 – 1.0). Job grading depending on classification and previous experience as either Researcher I (1C) or Researcher II (2B), salary according to MUNI internal wage regulations.
Job denoscription: participation in research (required) and teaching (negotiable), especially preparation of research reports/papers/conference presentations in the area of partnership formation/transitions/dissolution preferably examined from a comparative perspective and using data from the Generations and Gender Programme (GGP) or similar source.
Qualifications: M.A. degree or equivalent (prae-doc position) or a Ph.D. degree (post-doctoral position) in sociology, demography or other relevant field, experience with quantitative (specially survey/panel) data, very good command of English.
Application documents: Cover Letter indicating the date of earliest availability, Curriculum Vitae including a list of publications and conference presentations, copies of degree certificates.
Deadline for applications: December 15, 2019. Send your application as a single PDF file to the Czech GGP country office at ggp@fss.muni.cz.
✔️ @ApplyTime
Masaryk University seeks to appoint a doctoral student or a post-doctoral scholar in the Office of Population Studies and Department of Sociology as soon as possible, but no later than July 1, 2020.
The appointment is for 2 years, FTE is negotiable (between 0.5 – 1.0). Job grading depending on classification and previous experience as either Researcher I (1C) or Researcher II (2B), salary according to MUNI internal wage regulations.
Job denoscription: participation in research (required) and teaching (negotiable), especially preparation of research reports/papers/conference presentations in the area of partnership formation/transitions/dissolution preferably examined from a comparative perspective and using data from the Generations and Gender Programme (GGP) or similar source.
Qualifications: M.A. degree or equivalent (prae-doc position) or a Ph.D. degree (post-doctoral position) in sociology, demography or other relevant field, experience with quantitative (specially survey/panel) data, very good command of English.
Application documents: Cover Letter indicating the date of earliest availability, Curriculum Vitae including a list of publications and conference presentations, copies of degree certificates.
Deadline for applications: December 15, 2019. Send your application as a single PDF file to the Czech GGP country office at ggp@fss.muni.cz.
✔️ @ApplyTime
AI Scientist positions at AI Singapore
Hi all,
We have openings for AI Scientists and AI Scientific Officers.
AI Singapore (AISG) is a national program launched by the National Research Foundation (NRF). It brings together all Singapore-based research institutions and the vibrant ecosystem of AI start-ups and companies to perform use-inspired research, grow the knowledge, create the tools, and develop the talent to power Singapore's AI efforts. The AI Technology Team, led by Prof. Tze Yun Leong, Prof. Stefan Winkler, and Prof. Bryan Low, is looking for AI Scientists and Scientific Officers.
As an AI Scientist or Scientific Officer, you will conduct desk research to identify and propose research domains and topics of significant impact and priority. Working in close interaction with academic researchers and industry partners, you will assist AISG leadership in shaping future grant programs as well as reviewing and evaluating proposal submissions. You will also have the opportunity to engage in state-of-the-art research and contribute to the development of open source systems.
Qualifications:
a Ph.D. degree in computer science or related disciplines
extensive AI knowledge, especially in areas such as adversarial ML, federated learning, synthetic data generation, social network analysis, computer vision, natural language processing
excellent communication skills in both written and verbal English
keen interest in working with emerging technologies and frameworks
an adventurous spirit and willingness to learn new ideas and new domains
Benefits include:
Close collaboration with local universities, research institutes, and companies
Competitive compensation, including family health benefits
Live in a vibrant, multi-cultural city in the heart of South-East Asia
Please submit your application at www.aisingapore.org/careers
Best regards,
Stefan Winkler
aisingapore.org
AI Singapore (AISG)
innovation 4.0
3 Research Link #02-04
Singapore 117602
www.aisingapore.org | www.facebook.com/groups/aisingapore | www.linkedin.com/company/aisingapore
✔️ @ApplyTime
Hi all,
We have openings for AI Scientists and AI Scientific Officers.
AI Singapore (AISG) is a national program launched by the National Research Foundation (NRF). It brings together all Singapore-based research institutions and the vibrant ecosystem of AI start-ups and companies to perform use-inspired research, grow the knowledge, create the tools, and develop the talent to power Singapore's AI efforts. The AI Technology Team, led by Prof. Tze Yun Leong, Prof. Stefan Winkler, and Prof. Bryan Low, is looking for AI Scientists and Scientific Officers.
As an AI Scientist or Scientific Officer, you will conduct desk research to identify and propose research domains and topics of significant impact and priority. Working in close interaction with academic researchers and industry partners, you will assist AISG leadership in shaping future grant programs as well as reviewing and evaluating proposal submissions. You will also have the opportunity to engage in state-of-the-art research and contribute to the development of open source systems.
Qualifications:
a Ph.D. degree in computer science or related disciplines
extensive AI knowledge, especially in areas such as adversarial ML, federated learning, synthetic data generation, social network analysis, computer vision, natural language processing
excellent communication skills in both written and verbal English
keen interest in working with emerging technologies and frameworks
an adventurous spirit and willingness to learn new ideas and new domains
Benefits include:
Close collaboration with local universities, research institutes, and companies
Competitive compensation, including family health benefits
Live in a vibrant, multi-cultural city in the heart of South-East Asia
Please submit your application at www.aisingapore.org/careers
Best regards,
Stefan Winkler
aisingapore.org
AI Singapore (AISG)
innovation 4.0
3 Research Link #02-04
Singapore 117602
www.aisingapore.org | www.facebook.com/groups/aisingapore | www.linkedin.com/company/aisingapore
✔️ @ApplyTime
AI Singapore
Careers - AI Singapore
No active recruitments
University of Oulu International Scholarships 2020-2021
The University of Oulu International Scholarship Scheme provides scholarships to academically talented international students studying for a Master’s degree in the University of Oulu two-year International Master’s programmes or five -year Intercultural Teacher Education programme. The scholarships will be granted in the form of a tuition fee waiver covering 50% or 75% of the full tuition fee. Applicants can apply for the tuition scholarship as part of the admissions process. University of Oulu Scholarships do not cover living costs.
More info
✔️ @ApplyTime
The University of Oulu International Scholarship Scheme provides scholarships to academically talented international students studying for a Master’s degree in the University of Oulu two-year International Master’s programmes or five -year Intercultural Teacher Education programme. The scholarships will be granted in the form of a tuition fee waiver covering 50% or 75% of the full tuition fee. Applicants can apply for the tuition scholarship as part of the admissions process. University of Oulu Scholarships do not cover living costs.
More info
✔️ @ApplyTime
www.oulu.fi
Eligibility
Information on who can apply to our programmes and which degree you should hold
Dame Margaret Clark Scholarship in Political Science
Eligibility Criteria
Students eligible for this scholarship must:
Master’s by thesis students (120 points)
Have completed an honours degree in political science or international relations or a cognate discipline providing appropriate preparation for the completion a Master’s thesis and be enrolled in a full year (120 point) Master’s thesis in political science or international relations at Victoria University of Wellington.
Taught Masters students (180 points):
Be enrolled in a full year (180 point) taught Masters in political science or international relations at Victoria University of Wellington.
Selection for this scholarship will be based on academic merit, and in particular, the grades achieved in 300 and 400 level papers in political science or international relations. In the case of candidates with a similar grade point average, preference will be given to students undertaking a thesis on some aspect of New Zealand politics.
More info
✔️ @ApplyTime
Eligibility Criteria
Students eligible for this scholarship must:
Master’s by thesis students (120 points)
Have completed an honours degree in political science or international relations or a cognate discipline providing appropriate preparation for the completion a Master’s thesis and be enrolled in a full year (120 point) Master’s thesis in political science or international relations at Victoria University of Wellington.
Taught Masters students (180 points):
Be enrolled in a full year (180 point) taught Masters in political science or international relations at Victoria University of Wellington.
Selection for this scholarship will be based on academic merit, and in particular, the grades achieved in 300 and 400 level papers in political science or international relations. In the case of candidates with a similar grade point average, preference will be given to students undertaking a thesis on some aspect of New Zealand politics.
More info
✔️ @ApplyTime
RL and LfD research positions (now including interns) at Bosch / UT Austin, focusing on autonomous vehicles
Hi, everyone. We're now accepting applications for summer 2020 Research Interns at the following link: https://smrtr.io/3D3zr.
For the Research Scientist and Research Engineer positions I emailed about some weeks ago, we're nearing the end of the application period. We will only accept applications through the end of this week. Those roles can be applied to here:
Research Scientist - Machine Learning for Autonomous Driving Behavior: https://smrtr.io/3rgnH
Research Engineer - Machine Learning for Autonomous Driving Behavior: https://smrtr.io/3sqZZ
--Information on Bosch Austin--
I've recently begun building an RL/LfD-for-autonomous-vehicles research team for Bosch, the world's largest automotive supplier (with $51B in revenue in 2018), who also happens to make nice home appliances and power tools. Our team has an unusual setup: we office within the UT Austin Computer Science building and are collaborating with Peter Stone, Scott Niekum, and others here. We plan to publish research on RL and LfD topics---where autonomous driving may only be one of many applications of the research results---but we’ll also do R&D that adds algorithms to the Bosch autonomous vehicle program. In the mix are some human-in-the-loop RL research projects as well.
Here’s why I’m grateful to be in this group and why it’s a special opportunity for researchers focusing on RL or LfD for robotics. Features of Bosch in Austin:
an ability to move between fundamental and applied research
a focus on autonomous vehicles, a high-impact topic with problems spread across the spectrum of application and research
competitive industry pay in an academic setting
Austin (creative culture, natural beauty, and a low cost of living for a US tech hub) )
------------
Please send any questions to my Bosch email, brad.knox@us.bosch.com. Applications should be made through the links at top.
Best regards,
Brad
P.S. Apologies to anyone who receives multiple copies via cross posting.
____________________
W. Bradley Knox, PhD
http://bradknox.net
(+1) 512-542-3333
✔️ @ApplyTime
Hi, everyone. We're now accepting applications for summer 2020 Research Interns at the following link: https://smrtr.io/3D3zr.
For the Research Scientist and Research Engineer positions I emailed about some weeks ago, we're nearing the end of the application period. We will only accept applications through the end of this week. Those roles can be applied to here:
Research Scientist - Machine Learning for Autonomous Driving Behavior: https://smrtr.io/3rgnH
Research Engineer - Machine Learning for Autonomous Driving Behavior: https://smrtr.io/3sqZZ
--Information on Bosch Austin--
I've recently begun building an RL/LfD-for-autonomous-vehicles research team for Bosch, the world's largest automotive supplier (with $51B in revenue in 2018), who also happens to make nice home appliances and power tools. Our team has an unusual setup: we office within the UT Austin Computer Science building and are collaborating with Peter Stone, Scott Niekum, and others here. We plan to publish research on RL and LfD topics---where autonomous driving may only be one of many applications of the research results---but we’ll also do R&D that adds algorithms to the Bosch autonomous vehicle program. In the mix are some human-in-the-loop RL research projects as well.
Here’s why I’m grateful to be in this group and why it’s a special opportunity for researchers focusing on RL or LfD for robotics. Features of Bosch in Austin:
an ability to move between fundamental and applied research
a focus on autonomous vehicles, a high-impact topic with problems spread across the spectrum of application and research
competitive industry pay in an academic setting
Austin (creative culture, natural beauty, and a low cost of living for a US tech hub) )
------------
Please send any questions to my Bosch email, brad.knox@us.bosch.com. Applications should be made through the links at top.
Best regards,
Brad
P.S. Apologies to anyone who receives multiple copies via cross posting.
____________________
W. Bradley Knox, PhD
http://bradknox.net
(+1) 512-542-3333
✔️ @ApplyTime
Smartrecruiters
Bosch Group Research Intern - Austin, TX (Summer 2020) | SmartRecruiters
If selected, you will be part of our team at the new Bosch Austin site. The site is embedded in the University of Texas at Austin's Computer Science Department, with offices in the CS Department's beautiful new Gates Dell Complex.As part of your…
Postdoc - Immunology, Virology, Biology, Life Sciences - Oncolytic Viruses and Cancer Immunotherapy
Medizinische Universität Innsbruck Innsbruck (Österreich)
A Post Doc position is available at the Christian Doppler Laboratory for Viral Immunotherapy “CD-VIT”, part of the Institute for Virology at the Medical University of Innsbruck, Austria.
The Christian Doppler Laboratory for Viral Immunotherapy of Cancer is an international research group with strong translational focus on the development of novel cancer treatments. Our lab’s main aim is to integrate virotherapy into the dynamic field of cancer immunotherapy. We work in an academic environment in close collaboration with the pharmaceutical industry. We employ a broad range of methods including molecular virology and biology, advanced cytometry and tumor immunology, single cell sequencing, and in vivo models. Generous funding is provided by the Christian Doppler Research Association, Viratherapeutics GmbH and Boehringer Ingelheim Pharma.
Activities and responsibilities
The portfolio of the advertised Postdoc position includes - but is not limited to:
Characterization and modulation of immunogenic cell death induced by oncolytic viruses
Development of immune-modulating armed oncolytic viruses
Studying the mechanisms linking viral oncolysis with antitumor immunity
Qualification profile
Your profile:
Required qualifications include:
PhD degree in life sciences (biology/immunology/microbiology/pharmacology/biochemistry)
Strong experimental background in molecular virology OR immunogenic cell death
Strong motivation and commitment for the research project, dedication to work as a team player and supervise undergraduate and graduate students
The following experiences are a strong plus:
Experience with mouse tumor models or mouse immunology (incl. animal work certification, i.e. FELASA or equivalents)
Genome engineering techniques, viral cloning
Cell death pathways / signal transduction
We offer
Our offer:
Translational research to develop new cancer therapies in close collaboration with partners from clinical departments, biotech and pharma industry
Multi-disciplinary scientific environment
Training and development opportunities
Exciting and stimulating work atmosphere in an international research consortium
Project funded by a prestigious research grant (Christian Doppler Research Laboratory) for up to 7 years (2017-2024)
Annual salary around € 54,000.- gross
Appointment for 2 years initially, extension possible
Send application to
Please send your detailed application (including letter of motivation, curriculum vitae, copies of certificates, and references) by December 31th 2019 to the following address:
Dr Guido Wollmann
Institute for Virology
Medical University of Innsbruck
Peter-Mayr-Straße 4b
6020 Innsbruck
Austria
e-mail: guido.wollmann@i‐med.ac.at
✔️ @ApplyTime
Medizinische Universität Innsbruck Innsbruck (Österreich)
A Post Doc position is available at the Christian Doppler Laboratory for Viral Immunotherapy “CD-VIT”, part of the Institute for Virology at the Medical University of Innsbruck, Austria.
The Christian Doppler Laboratory for Viral Immunotherapy of Cancer is an international research group with strong translational focus on the development of novel cancer treatments. Our lab’s main aim is to integrate virotherapy into the dynamic field of cancer immunotherapy. We work in an academic environment in close collaboration with the pharmaceutical industry. We employ a broad range of methods including molecular virology and biology, advanced cytometry and tumor immunology, single cell sequencing, and in vivo models. Generous funding is provided by the Christian Doppler Research Association, Viratherapeutics GmbH and Boehringer Ingelheim Pharma.
Activities and responsibilities
The portfolio of the advertised Postdoc position includes - but is not limited to:
Characterization and modulation of immunogenic cell death induced by oncolytic viruses
Development of immune-modulating armed oncolytic viruses
Studying the mechanisms linking viral oncolysis with antitumor immunity
Qualification profile
Your profile:
Required qualifications include:
PhD degree in life sciences (biology/immunology/microbiology/pharmacology/biochemistry)
Strong experimental background in molecular virology OR immunogenic cell death
Strong motivation and commitment for the research project, dedication to work as a team player and supervise undergraduate and graduate students
The following experiences are a strong plus:
Experience with mouse tumor models or mouse immunology (incl. animal work certification, i.e. FELASA or equivalents)
Genome engineering techniques, viral cloning
Cell death pathways / signal transduction
We offer
Our offer:
Translational research to develop new cancer therapies in close collaboration with partners from clinical departments, biotech and pharma industry
Multi-disciplinary scientific environment
Training and development opportunities
Exciting and stimulating work atmosphere in an international research consortium
Project funded by a prestigious research grant (Christian Doppler Research Laboratory) for up to 7 years (2017-2024)
Annual salary around € 54,000.- gross
Appointment for 2 years initially, extension possible
Send application to
Please send your detailed application (including letter of motivation, curriculum vitae, copies of certificates, and references) by December 31th 2019 to the following address:
Dr Guido Wollmann
Institute for Virology
Medical University of Innsbruck
Peter-Mayr-Straße 4b
6020 Innsbruck
Austria
e-mail: guido.wollmann@i‐med.ac.at
✔️ @ApplyTime
Interested Student for Integrated MS and PhD position in Machine Learning
Dear Researchers and Professors,
Greetings! I am Md Emdad Ullah, looking for an Integrated Master's cum PhD studentship position across the globe in the areas of Artificial Intelligence, Machine Learning, Data Science, Natural Language Processing or in related areas of Computer Science.Specifically, I am interested in machine learning application in the chemical field.
I would expect a scholarship as I am planning to start this position as soon as possible.
Please let me know if you and/or any of your colleagues are interested in taking a student.
Thanking you. I look forward hearing from you soon.
Best Regards,
Md Emdad Ullah
University of Dhaks
email- emdadsami@gmail.com
✔️ @ApplyTime
Dear Researchers and Professors,
Greetings! I am Md Emdad Ullah, looking for an Integrated Master's cum PhD studentship position across the globe in the areas of Artificial Intelligence, Machine Learning, Data Science, Natural Language Processing or in related areas of Computer Science.Specifically, I am interested in machine learning application in the chemical field.
I would expect a scholarship as I am planning to start this position as soon as possible.
Please let me know if you and/or any of your colleagues are interested in taking a student.
Thanking you. I look forward hearing from you soon.
Best Regards,
Md Emdad Ullah
University of Dhaks
email- emdadsami@gmail.com
✔️ @ApplyTime
Permanent academic position - Lecturer/Senior Lecturer/Reader in Media & Data Science, University of Glasgow, School of Computing Science
Academic post available at Lecturer or Senior Lecturer/Reader (equivalent to Assistant or Associate Professor), subject to eligibility. The salary will be on the Research and Teaching Grade, level 7, 8 or 9: £35,210 - £39,610 / £43,266 - £50,132 / £51,630 - £58,089 per annum.
Applications for the post are welcome in any research areas of Information, Data and Analysis (IDA) Section of the school, including Machine Learning, Data Systems, Computational Interaction, Vision & sensor-based systems and Information Retrieval. The School has recently invested in a Media & Data Science research theme, recruiting experts in information retrieval and computational political/media science. The school now aims to further strengthen Media & Data Science theme by recruiting a post-holder that can complement the existing strengths within the School, and can develop, lead and sustain research of international standard in Artificial Intelligence/Machine Learning/Data Systems/Information Retrieval; contribute to teaching, assessment, project supervision and curriculum design at undergraduate and postgraduate levels; and participate in School management and organisation.
The School has existing strengths in machine learning and information retrieval applied in contexts such as Music Information Retrieval, Politics and Social media, Conversational interaction and Search. As part of our plans to expand our research and teaching activities in this area and collaborate more closely with our neighbours at BBC Scotland, the Section aims to recruit three academic posts in the topics of Machine Learning, Data Systems, Computational Interaction and Information Retrieval that have the potential to expand our existing strengths in media and data science, including but not limited to topics such as:
· core machine learning technologies (e.g. graph convolutional networks, architectures for multimedia (video or audio) content)
· conversational interaction and search
· explainability/interpretability/ethics/fairness in artificial intelligence, machine learning, algorithmic bias, especially applied in a media and search context
· data science for communications media
· data science for politics and social media
· social media analytics
· algorithmic content generation
· personalisation including (context-aware) recommendation systems/interaction
· large-scale data system engineering
Apply online at http://www.gla.ac.uk/explore/jobs/ Vacancy Reference: E20420
More details on positions available at: https://www.gla.ac.uk/schools/computing/worldchangerswelcome/priorityareas/#/mediaanddatascience
Closing date: 12th December 2019
The Information, Data and Analysis Section is led by Professor Roderick Murray-Smith, and has 17 academics, and 46 postdoctoral fellows, research assistants and PhD students active in this area. IDA section: https://www.gla.ac.uk/schools/computing/research/researchsections/ida-section/
For informal enquiries please contact:
Professor Rod Murray-Smith Email: Roderick.Murray-Smith@glasgow.ac.uk
Professor Roderick Murray-Smith
Head of Section, Information, Data and Analysis Section,
Inference, Dynamics and Interaction Research Group
School of Computing Science
University of Glasgow
Phone: +44 141 330 4984
Web: http://www.dcs.gla.ac.uk/~rod
✔️ @ApplyTime
Academic post available at Lecturer or Senior Lecturer/Reader (equivalent to Assistant or Associate Professor), subject to eligibility. The salary will be on the Research and Teaching Grade, level 7, 8 or 9: £35,210 - £39,610 / £43,266 - £50,132 / £51,630 - £58,089 per annum.
Applications for the post are welcome in any research areas of Information, Data and Analysis (IDA) Section of the school, including Machine Learning, Data Systems, Computational Interaction, Vision & sensor-based systems and Information Retrieval. The School has recently invested in a Media & Data Science research theme, recruiting experts in information retrieval and computational political/media science. The school now aims to further strengthen Media & Data Science theme by recruiting a post-holder that can complement the existing strengths within the School, and can develop, lead and sustain research of international standard in Artificial Intelligence/Machine Learning/Data Systems/Information Retrieval; contribute to teaching, assessment, project supervision and curriculum design at undergraduate and postgraduate levels; and participate in School management and organisation.
The School has existing strengths in machine learning and information retrieval applied in contexts such as Music Information Retrieval, Politics and Social media, Conversational interaction and Search. As part of our plans to expand our research and teaching activities in this area and collaborate more closely with our neighbours at BBC Scotland, the Section aims to recruit three academic posts in the topics of Machine Learning, Data Systems, Computational Interaction and Information Retrieval that have the potential to expand our existing strengths in media and data science, including but not limited to topics such as:
· core machine learning technologies (e.g. graph convolutional networks, architectures for multimedia (video or audio) content)
· conversational interaction and search
· explainability/interpretability/ethics/fairness in artificial intelligence, machine learning, algorithmic bias, especially applied in a media and search context
· data science for communications media
· data science for politics and social media
· social media analytics
· algorithmic content generation
· personalisation including (context-aware) recommendation systems/interaction
· large-scale data system engineering
Apply online at http://www.gla.ac.uk/explore/jobs/ Vacancy Reference: E20420
More details on positions available at: https://www.gla.ac.uk/schools/computing/worldchangerswelcome/priorityareas/#/mediaanddatascience
Closing date: 12th December 2019
The Information, Data and Analysis Section is led by Professor Roderick Murray-Smith, and has 17 academics, and 46 postdoctoral fellows, research assistants and PhD students active in this area. IDA section: https://www.gla.ac.uk/schools/computing/research/researchsections/ida-section/
For informal enquiries please contact:
Professor Rod Murray-Smith Email: Roderick.Murray-Smith@glasgow.ac.uk
Professor Roderick Murray-Smith
Head of Section, Information, Data and Analysis Section,
Inference, Dynamics and Interaction Research Group
School of Computing Science
University of Glasgow
Phone: +44 141 330 4984
Web: http://www.dcs.gla.ac.uk/~rod
✔️ @ApplyTime
PhD studentship in binocular vision at the University of York
Dear all,
A fully funded PhD studentship is available (Home/EU) at the University of York (UK) in the laboratory of Daniel Baker and Aurelio Bruno, beginning October 2020. The project is on the binocular integration of light, and will involve combining pupillometry, EEG and computational modelling to understand both cortical and subcortical processes of binocular signal combination. There will be opportunity to investigate how these processes might differ in clinical groups, including amblyopia and autism. Further details are available here:
https://www.findaphd.com/phds/project/binocular-integration-of-light-in-amblyopia-and-autism/?p115661
Please encourage talented undergraduate and masters students to apply.
All the best,
- Daniel Baker
✔️ @ApplyTime
Dear all,
A fully funded PhD studentship is available (Home/EU) at the University of York (UK) in the laboratory of Daniel Baker and Aurelio Bruno, beginning October 2020. The project is on the binocular integration of light, and will involve combining pupillometry, EEG and computational modelling to understand both cortical and subcortical processes of binocular signal combination. There will be opportunity to investigate how these processes might differ in clinical groups, including amblyopia and autism. Further details are available here:
https://www.findaphd.com/phds/project/binocular-integration-of-light-in-amblyopia-and-autism/?p115661
Please encourage talented undergraduate and masters students to apply.
All the best,
- Daniel Baker
✔️ @ApplyTime
PhD positions in Machine Learning in ECE at George Washington University, USA
Dr. Mahdi Imani, an assistant professor at the Department of Electrical and Computer Engineering at the George Washington University, seeks for multiple PhD students with interests in Machine Learning, Reinforcement Learning and Statistics. Ideal candidates may have:
- Master’s degree in electrical/computer engineering or computer science.
- Strong background in mathematics and statistics.
- Good programming skills (e.g., Python).
Prospective students may email their CV, trannoscripts and English test scores at imani.gwu@gmail.com. For more information, see https://web.seas.gwu.edu/imani/.
Self-supported postdoctoral and visiting scholars are encouraged to contact as well.
--
Mahdi Imani, Ph.D.
Assistant Professor
Dept. of Electrical and Computer Eng.
George Washington University
https://web.seas.gwu.edu/imani/
✔️ @ApplyTime
Dr. Mahdi Imani, an assistant professor at the Department of Electrical and Computer Engineering at the George Washington University, seeks for multiple PhD students with interests in Machine Learning, Reinforcement Learning and Statistics. Ideal candidates may have:
- Master’s degree in electrical/computer engineering or computer science.
- Strong background in mathematics and statistics.
- Good programming skills (e.g., Python).
Prospective students may email their CV, trannoscripts and English test scores at imani.gwu@gmail.com. For more information, see https://web.seas.gwu.edu/imani/.
Self-supported postdoctoral and visiting scholars are encouraged to contact as well.
--
Mahdi Imani, Ph.D.
Assistant Professor
Dept. of Electrical and Computer Eng.
George Washington University
https://web.seas.gwu.edu/imani/
✔️ @ApplyTime
2 PhD Candidates in Computer Science
paluno - The Ruhr Institute for Software Technology, Universität Duisburg-Essen
Activities and responsibilities
Are you passionate about SOFTWARE ENGINEERING research?
If so, you should apply for one of our positions.
Please let us know your research interest, the research challenge you like to work on, and your initial thoughts how to address the challenge.
We offer you:
a full-time position with a competitive salary according to the German TV-L (40,000-50,000 €/a)
dedicated travel and equipment budget
close collaboration with our partners from industry and academia in the context of our European and national research projects
an attractive and modern workplace with excellent facilities
intensive mentoring and a structured PhD process
English as working language
More info
✔️ @ApplyTime
paluno - The Ruhr Institute for Software Technology, Universität Duisburg-Essen
Activities and responsibilities
Are you passionate about SOFTWARE ENGINEERING research?
If so, you should apply for one of our positions.
Please let us know your research interest, the research challenge you like to work on, and your initial thoughts how to address the challenge.
We offer you:
a full-time position with a competitive salary according to the German TV-L (40,000-50,000 €/a)
dedicated travel and equipment budget
close collaboration with our partners from industry and academia in the context of our European and national research projects
an attractive and modern workplace with excellent facilities
intensive mentoring and a structured PhD process
English as working language
More info
✔️ @ApplyTime
3-year fully funded PhD position on Multimodal Machine Learning for Mental Health (CNRS GREYC, France)
The Human Language Technology research group of the CNRS GREYC
Laboratory (https://www.greyc.fr) invites applications for one fully
funded three-year PhD position in Multimodal (acoustics, visual, text)
Machine Learning for Mental Health.
The CNRS GREYC Laboratory carries out research activities in the field
of digital sciences covering several aspects of computer science
including image processing, data mining, artificial intelligence,
computer security, mathematical computing, natural language processing,
electronics and instrumentation. The laboratory gathers more than 200
members in Caen, Normandy.
The successful candidate must hold a Master degree or equivalent in Data
Science, Applied Mathematics or Computer Science. A strong background in
(statistical, deep) machine learning is required as well as knowledge in
natural language processing or/and computer vision.
If you are interested by this position, please send the following
information to Gaël Dias (gael.dias@unicaen.fr):
- Detailed CV
- Trannoscripts of Bsc. and Msc. degrees
- Recommendation letters (up to 3)
Applications will be studied until the position is fullfilled or before
31st March 2020.
For more information, you can directly contact Gaël Dias
(gael.dias@unicaen.fr).
Best regards,
Gaël Dias.
✔️ @ApplyTime
The Human Language Technology research group of the CNRS GREYC
Laboratory (https://www.greyc.fr) invites applications for one fully
funded three-year PhD position in Multimodal (acoustics, visual, text)
Machine Learning for Mental Health.
The CNRS GREYC Laboratory carries out research activities in the field
of digital sciences covering several aspects of computer science
including image processing, data mining, artificial intelligence,
computer security, mathematical computing, natural language processing,
electronics and instrumentation. The laboratory gathers more than 200
members in Caen, Normandy.
The successful candidate must hold a Master degree or equivalent in Data
Science, Applied Mathematics or Computer Science. A strong background in
(statistical, deep) machine learning is required as well as knowledge in
natural language processing or/and computer vision.
If you are interested by this position, please send the following
information to Gaël Dias (gael.dias@unicaen.fr):
- Detailed CV
- Trannoscripts of Bsc. and Msc. degrees
- Recommendation letters (up to 3)
Applications will be studied until the position is fullfilled or before
31st March 2020.
For more information, you can directly contact Gaël Dias
(gael.dias@unicaen.fr).
Best regards,
Gaël Dias.
✔️ @ApplyTime
Research Fellow / Senior Research Fellow at the intersection of machine learning and robotics
We are looking for a Research Fellow / Senior Research Fellow at the intersection of robotics and machine learning.
We are looking for a (Senior) Research Fellow at the intersection of robotics and machine learning.
Autonomous robots will play an increasingly important role in the future, e.g., in the context of healthcare, space exploration, or supporting humans in day-to-day activities. Key challenges, autonomous robots face are that they need to be able to learn from data and adapt fast to new situations without strong human interventions. Currently, autonomous learning systems either require vast amounts of data or they require human guidance. This project centers around approaches for data-efficient autonomous learning for robotics, e.g., by means of probabilistic modeling, transfer learning or using generic priors that constrain the learning system.
You will be part of the Statistical Machine Learning Group, which is located at UCL's Centre for Artificial Intelligence. We have a strong background in probabilistic modeling, data-efficient machine learning, and reinforcement learning. The successful applicant will lead and contribute to research projects at the intersection of statistical machine learning and climate science. They are also expected to contribute to student supervision and interact with research and project partners. The key objective is to design and evaluate machine learning approaches to advance the current state of the art in robot learning.
The post is graded as Grade 7 or Grade 8, with starting salary in the range £35,965 to £43,470 (Grade 7) or £44,674 to £52,701 (Grade 8) per annum (including London Allowance). Progression through the salary scale is incremental.
The funding for this post is for 24 months in the first instance.
The successful applicant will have a PhD (or close to be obtaining a PhD) in machine learning, statistics, computer science, robotics or a relevant area. They should have a track record of internationally recognized research and be able to work as part of a team. Research skills (theoretical and empirical, planning and documentary) plus effective written and verbal communication skills are essential.
More details and a link to the application can be found at
Please contact me if you have questions: m.deisenroth@ucl.ac.uk
I will also be at NeurIPS this month, and I'm happy to discuss opportunities in person.
✔️ @ApplyTime
We are looking for a Research Fellow / Senior Research Fellow at the intersection of robotics and machine learning.
We are looking for a (Senior) Research Fellow at the intersection of robotics and machine learning.
Autonomous robots will play an increasingly important role in the future, e.g., in the context of healthcare, space exploration, or supporting humans in day-to-day activities. Key challenges, autonomous robots face are that they need to be able to learn from data and adapt fast to new situations without strong human interventions. Currently, autonomous learning systems either require vast amounts of data or they require human guidance. This project centers around approaches for data-efficient autonomous learning for robotics, e.g., by means of probabilistic modeling, transfer learning or using generic priors that constrain the learning system.
You will be part of the Statistical Machine Learning Group, which is located at UCL's Centre for Artificial Intelligence. We have a strong background in probabilistic modeling, data-efficient machine learning, and reinforcement learning. The successful applicant will lead and contribute to research projects at the intersection of statistical machine learning and climate science. They are also expected to contribute to student supervision and interact with research and project partners. The key objective is to design and evaluate machine learning approaches to advance the current state of the art in robot learning.
The post is graded as Grade 7 or Grade 8, with starting salary in the range £35,965 to £43,470 (Grade 7) or £44,674 to £52,701 (Grade 8) per annum (including London Allowance). Progression through the salary scale is incremental.
The funding for this post is for 24 months in the first instance.
The successful applicant will have a PhD (or close to be obtaining a PhD) in machine learning, statistics, computer science, robotics or a relevant area. They should have a track record of internationally recognized research and be able to work as part of a team. Research skills (theoretical and empirical, planning and documentary) plus effective written and verbal communication skills are essential.
More details and a link to the application can be found at
Please contact me if you have questions: m.deisenroth@ucl.ac.uk
I will also be at NeurIPS this month, and I'm happy to discuss opportunities in person.
✔️ @ApplyTime
Two postdoctoral positions are available in the lab of Carlos Fernandez-Granda at the Courant Institute and Center for Data Science at NYU:
- Machine learning for healthcare: The focus is the design of deep-learning methodology for medical applications, with emphasis on domain adaptation, high-dimensional signal processing, and semi-supervised learning. The developed techniques will be applied to automatic quantification of rehabilitation dose in stroke patients from sensor and camera data, in collaboration with the Mobilis Lab in the Department of Neurology at NYU School of Medicine, which aims to enhance motor recovery after stroke.
Link: https://apply.interfolio.com/66997
- Machine learning for dynamical systems: The focus is the design of machine-learning methodology for the analysis of dynamic systems, with potential applications to computer vision, material science and molecular biology.
Link: https://apply.interfolio.com/69741
Qualifications
Candidates should possess a Ph.D. in Computer Science, Electrical Engineering, Data Science, or related disciplines. In addition, they should have a strong background in machine learning, and solid programming skills. They must have the ability to work independently and with an interdisciplinary team.
Application Instructions
Interested candidates should submit (1) a CV, (2) a brief cover letter explaining their research experience, how their interests would fit the goals of the project, career plans, and available start date, and (3) the names and contact information of three references familiar with the applicant’s research and academic work.
✔️ @ApplyTime
- Machine learning for healthcare: The focus is the design of deep-learning methodology for medical applications, with emphasis on domain adaptation, high-dimensional signal processing, and semi-supervised learning. The developed techniques will be applied to automatic quantification of rehabilitation dose in stroke patients from sensor and camera data, in collaboration with the Mobilis Lab in the Department of Neurology at NYU School of Medicine, which aims to enhance motor recovery after stroke.
Link: https://apply.interfolio.com/66997
- Machine learning for dynamical systems: The focus is the design of machine-learning methodology for the analysis of dynamic systems, with potential applications to computer vision, material science and molecular biology.
Link: https://apply.interfolio.com/69741
Qualifications
Candidates should possess a Ph.D. in Computer Science, Electrical Engineering, Data Science, or related disciplines. In addition, they should have a strong background in machine learning, and solid programming skills. They must have the ability to work independently and with an interdisciplinary team.
Application Instructions
Interested candidates should submit (1) a CV, (2) a brief cover letter explaining their research experience, how their interests would fit the goals of the project, career plans, and available start date, and (3) the names and contact information of three references familiar with the applicant’s research and academic work.
✔️ @ApplyTime
Research Associate Water Chemistry
Technische Universität Dresden
At the TU Dresden, faculty of Environmental Sciences, Department of Hydro Sciences, the Institute of Water Chemistry offers, as soon as possible, a position as
Research Associate
(Subject to personal qualification employees are remunerated according to salary group E 13 TV-L)
lasting to the end of the project on 31.12.2022 which entails 65 % of the fulltime weekly hours. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeit-vertragsgesetz - WissZeitVG). The position offers the chance to obtain further academic qualification (e.g. PhD).
Within the framework of an ESF funded junior research group, it is the aim to develop a system for peptide-based cell-cell communication between yeasts and bacteria for technological processes. A priority objective shall be the comprehensive elucidation of control mechanisms, which are necessary for a balanced cultivation of microbial communities and the optimal exchange of metabolites, in order to enable a conscious use of those mechanisms.
Activities and responsibilities
Establishing analytical methods for the quantification of signal peptides (pheromones) using HPLC-MS/MS and modification thereof in order to meet the needs of more complex matrices and low concentrations, including pre-analytical approaches like SPE, GPC/SEC or ultrafiltration; furthermore, the quantitative determination of selected antibiotics in water and culture media samples, the deduction of kinetic data concerning the biochemical degradation of antibiotics and the characterisation of transformation products.
Qualification profile
Junior researcher, a very good university degree in the fields of chemistry, biochemistry, food chemistry, environmental sciences or similar, obtained no longer than 4 years ago (plus e.g. times of parental leave); a high level of motivation and interest in scientific and interdisciplinary research; very good knowledge of English language (written and spoken); ability to work independently and well-structured in a team with a high level of communication and cooperation within the junior research group; analytical thinking; exceptional skills in laboratory work as well as a deep understanding within the field of analytical chemistry (especially determination of peptides and antibiotics using HPLC-MS/MS, sample preparation), hydrochemistry, biochemistry and microbiology.
Send application to
Please, send your expressive application including all common documents by 09.01.2020 (stamped arrival date of the university central mail service applies) to TU Dresden, Fakultät Umweltwissenschaften, Fachrichtung Hydrowissenschaften, Institut für Wasserchemie, Herrn Prof. Dr. Stefan Stolte, Helmholtzstr. 10, 01069 Dresden. Please submit copies only, as your application will not be returned to you. Expenses incurred in attending interviews cannot be reimbursed.
Reference to data protection: Your data protection rights, the purpose for which your data will be processed, as well as further information about data protection is available to you on the website: https://tu-dresden.de/karriere/datenschutzhinweis
✔️ @ApplyTime
Technische Universität Dresden
At the TU Dresden, faculty of Environmental Sciences, Department of Hydro Sciences, the Institute of Water Chemistry offers, as soon as possible, a position as
Research Associate
(Subject to personal qualification employees are remunerated according to salary group E 13 TV-L)
lasting to the end of the project on 31.12.2022 which entails 65 % of the fulltime weekly hours. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeit-vertragsgesetz - WissZeitVG). The position offers the chance to obtain further academic qualification (e.g. PhD).
Within the framework of an ESF funded junior research group, it is the aim to develop a system for peptide-based cell-cell communication between yeasts and bacteria for technological processes. A priority objective shall be the comprehensive elucidation of control mechanisms, which are necessary for a balanced cultivation of microbial communities and the optimal exchange of metabolites, in order to enable a conscious use of those mechanisms.
Activities and responsibilities
Establishing analytical methods for the quantification of signal peptides (pheromones) using HPLC-MS/MS and modification thereof in order to meet the needs of more complex matrices and low concentrations, including pre-analytical approaches like SPE, GPC/SEC or ultrafiltration; furthermore, the quantitative determination of selected antibiotics in water and culture media samples, the deduction of kinetic data concerning the biochemical degradation of antibiotics and the characterisation of transformation products.
Qualification profile
Junior researcher, a very good university degree in the fields of chemistry, biochemistry, food chemistry, environmental sciences or similar, obtained no longer than 4 years ago (plus e.g. times of parental leave); a high level of motivation and interest in scientific and interdisciplinary research; very good knowledge of English language (written and spoken); ability to work independently and well-structured in a team with a high level of communication and cooperation within the junior research group; analytical thinking; exceptional skills in laboratory work as well as a deep understanding within the field of analytical chemistry (especially determination of peptides and antibiotics using HPLC-MS/MS, sample preparation), hydrochemistry, biochemistry and microbiology.
Send application to
Please, send your expressive application including all common documents by 09.01.2020 (stamped arrival date of the university central mail service applies) to TU Dresden, Fakultät Umweltwissenschaften, Fachrichtung Hydrowissenschaften, Institut für Wasserchemie, Herrn Prof. Dr. Stefan Stolte, Helmholtzstr. 10, 01069 Dresden. Please submit copies only, as your application will not be returned to you. Expenses incurred in attending interviews cannot be reimbursed.
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