سلام برهمگی
اگه از دوستان کسی علاقهمنده که تیم کوچیکی تشکیل بدیم و در چالش زیر شرکت کنیم، لطفا به من ایمیل بزنه.
https://www.aicrowd.com/challenges/the-neural-mmo-challenge
این چالش سختیه، و جدا از برنامه نویسی قوی در زمینهی آر اِل، نیاز به دانش خوبی در زمینهی مالتی ایجنت آر اِل هم داره. در نتیجه اگه واقعا در این زمینه تجربه دارین لطفا ایمیل بزنین. در غیر این صورت شاید بهتر باشه که وقتمون رو در جای دیگهای بذاریم که بهرهوری بیشتری داشته باشه.
ارادتمند
اگه از دوستان کسی علاقهمنده که تیم کوچیکی تشکیل بدیم و در چالش زیر شرکت کنیم، لطفا به من ایمیل بزنه.
https://www.aicrowd.com/challenges/the-neural-mmo-challenge
این چالش سختیه، و جدا از برنامه نویسی قوی در زمینهی آر اِل، نیاز به دانش خوبی در زمینهی مالتی ایجنت آر اِل هم داره. در نتیجه اگه واقعا در این زمینه تجربه دارین لطفا ایمیل بزنین. در غیر این صورت شاید بهتر باشه که وقتمون رو در جای دیگهای بذاریم که بهرهوری بیشتری داشته باشه.
ارادتمند
AIcrowd | The Neural-MMO Challenge | Challenges
Robustness and teamwork in a massively multiagent environment
Post-doc/PhD positions in Robot Learning at Purdue CS
The Cognitive Robot Autonomy and Learning (CoRAL) Lab at the Department of Computer Science, Purdue University, under the direction of Prof. Ahmed Qureshi (https://qureshiahmed.github.io/), is looking for filling open Postdoc/PhD positions immediately until the end of the year for the robot learning research. We perform research at the intersection of robotics, machine learning, and artificial intelligence with a focus on scalable motion planning and control, manipulation, navigation, task planning, state-estimation, tactile perception, localization and mapping, active sensing, and sim-to-real transfer. We design, develop, and extend theory from the fields of deep learning, reinforcement learning, optimal control, computer vision, game theory, optimization, graphical models, statistics, information theory, physics, cognitive science, and computer graphics.
The accepted candidates will conduct independent research and publish high-impact factor journals and top robotics, computer vision, and machine learning conference papers. To apply, please fill out this form and send a single PDF of the following documents to ahqureshi.purdue@gmail.com:
a cover letter
university trannoscripts
names and contact information of three references
copies of up to three of your relevant scientific papers
Applicants are encouraged to include a link to their personal website or multimedia portfolio. Send applications and specific questions to
ahqureshi.purdue@gmail.com and have the subject line "[jobs] (PhD or
Postdoc) - your name".
Thank you,
🔭 @DeepGravity
The Cognitive Robot Autonomy and Learning (CoRAL) Lab at the Department of Computer Science, Purdue University, under the direction of Prof. Ahmed Qureshi (https://qureshiahmed.github.io/), is looking for filling open Postdoc/PhD positions immediately until the end of the year for the robot learning research. We perform research at the intersection of robotics, machine learning, and artificial intelligence with a focus on scalable motion planning and control, manipulation, navigation, task planning, state-estimation, tactile perception, localization and mapping, active sensing, and sim-to-real transfer. We design, develop, and extend theory from the fields of deep learning, reinforcement learning, optimal control, computer vision, game theory, optimization, graphical models, statistics, information theory, physics, cognitive science, and computer graphics.
The accepted candidates will conduct independent research and publish high-impact factor journals and top robotics, computer vision, and machine learning conference papers. To apply, please fill out this form and send a single PDF of the following documents to ahqureshi.purdue@gmail.com:
a cover letter
university trannoscripts
names and contact information of three references
copies of up to three of your relevant scientific papers
Applicants are encouraged to include a link to their personal website or multimedia portfolio. Send applications and specific questions to
ahqureshi.purdue@gmail.com and have the subject line "[jobs] (PhD or
Postdoc) - your name".
Thank you,
🔭 @DeepGravity
PhD position at the university of Neuchatel
We are looking for a PhD student to join our group on reinforcement learning and decision making at the University of Neuchatel, Switzerland ( https://www.unine.ch/ ). We are particularly interested in candidates with a strong mathematical background. Prior research experience as documented by your Masters thesis will be an additional bonus. Although any area in the intersection of machine learning, statistics and artificial intelligence may be considered, we are primarily looking for a student with a sincere interest in one or more of the following areas:
1. Reinforcement learning
2. Privacy (e.g. differential privacy)
3. Fairness in machine learning.
Examples of our group's past and current research can be found on arxiv: https://arxiv.org/search/?searchtype=author&query=Dimitrakakis%2C+C. The student will have the opportunity to visit and work with other group members at the University of Oslo, Norway ( https://www.mn.uio.no/ifi/english/people/aca/chridim/index.html ) and Chalmers University of Technology, Sweden ( http://www.cse.chalmers.se/~chrdimi/ ). The position is available from 1 Februrary 2022.
For further information, please contact me directly at christos.dimitrakakis@gmail.com with the subject 'PhD Neuchatel'.
🔭 @DeepGravity
We are looking for a PhD student to join our group on reinforcement learning and decision making at the University of Neuchatel, Switzerland ( https://www.unine.ch/ ). We are particularly interested in candidates with a strong mathematical background. Prior research experience as documented by your Masters thesis will be an additional bonus. Although any area in the intersection of machine learning, statistics and artificial intelligence may be considered, we are primarily looking for a student with a sincere interest in one or more of the following areas:
1. Reinforcement learning
2. Privacy (e.g. differential privacy)
3. Fairness in machine learning.
Examples of our group's past and current research can be found on arxiv: https://arxiv.org/search/?searchtype=author&query=Dimitrakakis%2C+C. The student will have the opportunity to visit and work with other group members at the University of Oslo, Norway ( https://www.mn.uio.no/ifi/english/people/aca/chridim/index.html ) and Chalmers University of Technology, Sweden ( http://www.cse.chalmers.se/~chrdimi/ ). The position is available from 1 Februrary 2022.
For further information, please contact me directly at christos.dimitrakakis@gmail.com with the subject 'PhD Neuchatel'.
🔭 @DeepGravity
Université de Neuchâtel
Venez étudier à l'Université de Neuchâtel. Découvrez nos quatre facultés et nos nombreuses formations en bachelor et en master.
یکی از بهترین پوزیشنهای دکتری ماشینلرنینگ دنیا، این پروگرام مشترک بین پلیتکنیک زوریخ و مکسپلانک آلمانه. اگه شرایطش رو دارین، پیشنهاد میکنم اپلای کنین:
https://www.jobs.ethz.ch/job/view/4709
🔭 @DeepGravity
https://www.jobs.ethz.ch/job/view/4709
🔭 @DeepGravity
www.jobs.ethz.ch
Funded Ph.D. Positions at the Max Planck ETH Center for Learning Systems
Stochmod EURO PhD School
Reinforcement learning applied to operations research: 10.12.-17.12.2021
http://stochmod.eu/EPS/
In this PhD school we want to build a bridge between Markov Decision Processes (MDP) and Reinforcement Learning (RL) and give OR students studying or using MDP’s the possibility to learn about RL techniques. RL can be seen as a collection of techniques or heuristics to solve large-scale MDP’s. It is a part of computer science and developed mostly independently from MDPs. RL is part of machine learning, together with unsupervised and supervised learning. After the current boom of supervised learning, with deep learning as its prime example, RL is expected to be the next big thing. For example, it is the technology that enables autonomous vehicles to think ahead, and it is equally important as deep learning which is used for image recognition. In this school we want to invite a few speakers from RL to teach us the methods and typical applications of RL. Then we will apply this to some problems that come from OR. We will take time to implement some of the algorithms to make sure the methods are well understood and to test them on some relatively easy instances of typical OR problems.
Important Dates:
Application: until 25th of September 2021
Notification of acceptance: 5th of October 2021
Formal registration: until 15th of October 2021
Workshop (online participation not possible!): 10th to 17th of December 2021
More information: http://stochmod.eu/EPS/
🔭 @DeepGravity
Reinforcement learning applied to operations research: 10.12.-17.12.2021
http://stochmod.eu/EPS/
In this PhD school we want to build a bridge between Markov Decision Processes (MDP) and Reinforcement Learning (RL) and give OR students studying or using MDP’s the possibility to learn about RL techniques. RL can be seen as a collection of techniques or heuristics to solve large-scale MDP’s. It is a part of computer science and developed mostly independently from MDPs. RL is part of machine learning, together with unsupervised and supervised learning. After the current boom of supervised learning, with deep learning as its prime example, RL is expected to be the next big thing. For example, it is the technology that enables autonomous vehicles to think ahead, and it is equally important as deep learning which is used for image recognition. In this school we want to invite a few speakers from RL to teach us the methods and typical applications of RL. Then we will apply this to some problems that come from OR. We will take time to implement some of the algorithms to make sure the methods are well understood and to test them on some relatively easy instances of typical OR problems.
Important Dates:
Application: until 25th of September 2021
Notification of acceptance: 5th of October 2021
Formal registration: until 15th of October 2021
Workshop (online participation not possible!): 10th to 17th of December 2021
More information: http://stochmod.eu/EPS/
🔭 @DeepGravity
16 funded positions in artificial intelligence & machine learning for postdocs, research fellows, PhD students
Join us to work on new machine learning techniques at the Finnish Center for Artificial Intelligence FCAI! We have exciting topics available around the following areas of research: (1) reinforcement learning, (2) probabilistic methods, (3) simulator-based inference, (4) privacy and federated learning, and (5) multi-agent modeling. Your work can be theoretical or applied, or both.
The deadline for the postdoc/research fellow applications is on August 21 and for the PhD student applications on August 28, 2022. Read more and apply here: https://fcai.fi/we-are-hiring
🔭 @DeepGravity
Join us to work on new machine learning techniques at the Finnish Center for Artificial Intelligence FCAI! We have exciting topics available around the following areas of research: (1) reinforcement learning, (2) probabilistic methods, (3) simulator-based inference, (4) privacy and federated learning, and (5) multi-agent modeling. Your work can be theoretical or applied, or both.
The deadline for the postdoc/research fellow applications is on August 21 and for the PhD student applications on August 28, 2022. Read more and apply here: https://fcai.fi/we-are-hiring
🔭 @DeepGravity
FCAI
Winter 2025 - Researcher positions in AI and machine learning — FCAI
PhD positions in computer science (machine learning and computer vision)
We are looking for students and researchers interested in the intersection of computer vision and machine learning for different application domains (e.g., robotics, sports, healthcare, manufacturing, multimedia, etc. ) at the University of Udine.
There are available positions for students who would like to pursue a Ph.D. in Computer Science and Artificial Intelligence and address the problem of "Deep Learning and Computer Vision".
Successful applicants will work with our Machine Learning and Perception group as well as with international partners where to spend 6 months abroad period.
The deadline for the application is *July 20, 2022*.
Full details about the application can be found here: https://www.uniud.it/en/research/doctorate-res/ammissione/active-notice/luglio?set_language=en
For further information or discussion, you can contact me at christian.micheloni@uniud.it
Computer Vision and Machine Learning (CVML) email list www page: https://lists.auth.gr/sympa/info/cvml
1) To post a message (in English) to CVML please: send an email to cvml@lists.auth.gr with subject: [Topic] Your_subject
[Topic] should be one of the following ones: [Jobs], [Conferences], [Journals], [Courses], [Studies], [News].
2) To subscribe (for free) to this Computer Vision and Machine Learning (CVML) email list and send/receive scientific messages/news, please:
send an empty email to sympa@lists.auth.gr with subject: subscribe cvml@lists.auth.gr your_name
3) To unsubscribe any time, send an empty email to sympa@lists.auth.gr with subject: unsubscribe cvml@lists.auth.gr
4) If you have any questions related to CVML list please contact: koroniioanna@csd.auth.gr List moderation is supervised by Prof. I.Pitas (pitas@csd.auth.gr). 🔭 @DeepGravity
We are looking for students and researchers interested in the intersection of computer vision and machine learning for different application domains (e.g., robotics, sports, healthcare, manufacturing, multimedia, etc. ) at the University of Udine.
There are available positions for students who would like to pursue a Ph.D. in Computer Science and Artificial Intelligence and address the problem of "Deep Learning and Computer Vision".
Successful applicants will work with our Machine Learning and Perception group as well as with international partners where to spend 6 months abroad period.
The deadline for the application is *July 20, 2022*.
Full details about the application can be found here: https://www.uniud.it/en/research/doctorate-res/ammissione/active-notice/luglio?set_language=en
For further information or discussion, you can contact me at christian.micheloni@uniud.it
Computer Vision and Machine Learning (CVML) email list www page: https://lists.auth.gr/sympa/info/cvml
1) To post a message (in English) to CVML please: send an email to cvml@lists.auth.gr with subject: [Topic] Your_subject
[Topic] should be one of the following ones: [Jobs], [Conferences], [Journals], [Courses], [Studies], [News].
2) To subscribe (for free) to this Computer Vision and Machine Learning (CVML) email list and send/receive scientific messages/news, please:
send an empty email to sympa@lists.auth.gr with subject: subscribe cvml@lists.auth.gr your_name
3) To unsubscribe any time, send an empty email to sympa@lists.auth.gr with subject: unsubscribe cvml@lists.auth.gr
4) If you have any questions related to CVML list please contact: koroniioanna@csd.auth.gr List moderation is supervised by Prof. I.Pitas (pitas@csd.auth.gr). 🔭 @DeepGravity
Università degli Studi di Udine
Call for Applications for the admission to the PhD programmes (39° Cycle) European Social Found Plus 2021/2027 (FSE+) - PS 22/23…
Ph.D. Programmes of the University of Udine: Accounting and Management, Law and Innovation in the European Legal Space, Computer Science and Artificial Intelligence, Industrial and Information Engineering, Molecular Medicine, Food Science, Environmental…
Researcher in Explainable AI and Medical Natural Language Processing (KU Leuven, Belgium)
We offer a two-year research position for a postdoctoral or predoctoral scientist on the topic of explainable AI in the context of natural language processing of clinical reports at the Department of Computer Science, KU Leuven. The position is financed by the CHIST-ERA project ANTIDOTE (ArgumeNtaTIon-Driven explainable artificial intelligence fOr digiTal mEdicine). The project focuses on deep learning models for text classification in the medical domain, where the need for high quality explanations of clinical decisions is critical. The project proposes an integrated approach for the understanding of textual medical data and the generation of a textual explanation to justify a medical diagnosis made by a neural network, so that clinicians can judge its validity.
The partners of the ANTIDOTE project provide annotated argumentative structures of natural language explanations of medical decisions (human explanations).
We will also leverage larger-scale data (without annotated explanations) in order to improve explanation generation. To guide explanation generation we will use feature importance techniques (integrated gradients, attention mechanisms, or search-based methods).
KU Leuven is declared the most innovative university in Europe for the fourth year in a row (Reuters) and is ranked 42th on the Times Higher Education World University Ranking (2022).
Offer
We offer a research position for 2 years starting September 1 or the latest October 1, 2022.
We offer a competitive wage and yearly budget to attend conferences.
We offer the opportunity for personal development beyond research including the supervision of master and PhD students and the possibility to contribute to teaching.
We offer access to our deep learning cluster which contains the latest GPU hardware.
Responsibilities
Perform fundamental research in natural language processing, machine learning and explainable AI resulting in publications in highly-ranked venues.
Collaborate with the other European partners of the ANTIDOTE project.
Profile
You have (or are near completion of) a master or PhD in Computer Science.
Given that we have to fill in the research position very soon, we will only consider applicants who can work in the European Union without a visa application.
You have a demonstrated expertise in machine learning, deep neural networks and natural language processing. Expertise in structured prediction and/or structured generation is a plus.
You have an outstanding track record of publications in relevant international peer-reviewed A ranked conferences and in journals with high impact factor in the fields of machine learning and natural language processing.
You are good at collaborating with others.
You work proactively and independently and have good communication skills.
You have an excellent knowledge of the English language, both spoken and written as well as of another European language (e.g., French, Spanish or Italian).
You are highly motivated, ambitious and result-oriented.
If interested, please apply the latest by July 31, 2022 by sending your CV and motivation letter to Dr. Damien Sileo (damien.sileo@kuleuven.be) or Prof. Dr. Marie-Francine Moens (sien.moens@kuleuven.be). Excellent candidates will be invited for an online interview. The position will be closed once a suitable candidate is found. For more information please contact Dr. Damien Sileo (damien.sileo@kuleuven.be) or Prof. Dr. Marie-Francine Moens (sien.moens@kuleuven.be).
🔭 @DeepGravity
We offer a two-year research position for a postdoctoral or predoctoral scientist on the topic of explainable AI in the context of natural language processing of clinical reports at the Department of Computer Science, KU Leuven. The position is financed by the CHIST-ERA project ANTIDOTE (ArgumeNtaTIon-Driven explainable artificial intelligence fOr digiTal mEdicine). The project focuses on deep learning models for text classification in the medical domain, where the need for high quality explanations of clinical decisions is critical. The project proposes an integrated approach for the understanding of textual medical data and the generation of a textual explanation to justify a medical diagnosis made by a neural network, so that clinicians can judge its validity.
The partners of the ANTIDOTE project provide annotated argumentative structures of natural language explanations of medical decisions (human explanations).
We will also leverage larger-scale data (without annotated explanations) in order to improve explanation generation. To guide explanation generation we will use feature importance techniques (integrated gradients, attention mechanisms, or search-based methods).
KU Leuven is declared the most innovative university in Europe for the fourth year in a row (Reuters) and is ranked 42th on the Times Higher Education World University Ranking (2022).
Offer
We offer a research position for 2 years starting September 1 or the latest October 1, 2022.
We offer a competitive wage and yearly budget to attend conferences.
We offer the opportunity for personal development beyond research including the supervision of master and PhD students and the possibility to contribute to teaching.
We offer access to our deep learning cluster which contains the latest GPU hardware.
Responsibilities
Perform fundamental research in natural language processing, machine learning and explainable AI resulting in publications in highly-ranked venues.
Collaborate with the other European partners of the ANTIDOTE project.
Profile
You have (or are near completion of) a master or PhD in Computer Science.
Given that we have to fill in the research position very soon, we will only consider applicants who can work in the European Union without a visa application.
You have a demonstrated expertise in machine learning, deep neural networks and natural language processing. Expertise in structured prediction and/or structured generation is a plus.
You have an outstanding track record of publications in relevant international peer-reviewed A ranked conferences and in journals with high impact factor in the fields of machine learning and natural language processing.
You are good at collaborating with others.
You work proactively and independently and have good communication skills.
You have an excellent knowledge of the English language, both spoken and written as well as of another European language (e.g., French, Spanish or Italian).
You are highly motivated, ambitious and result-oriented.
If interested, please apply the latest by July 31, 2022 by sending your CV and motivation letter to Dr. Damien Sileo (damien.sileo@kuleuven.be) or Prof. Dr. Marie-Francine Moens (sien.moens@kuleuven.be). Excellent candidates will be invited for an online interview. The position will be closed once a suitable candidate is found. For more information please contact Dr. Damien Sileo (damien.sileo@kuleuven.be) or Prof. Dr. Marie-Francine Moens (sien.moens@kuleuven.be).
🔭 @DeepGravity
PhD Research Position, Humboldt University, Berlin, Germany
Real-Time 3D Vision for Microscopy
https://www.informatik.hu-berlin.de/de/forschung/gebiete/viscom/open-research-position-fonda
Within the Collaborative Research Center Fonda, the Visual Computing
Group at Humboldt University is looking for an enthusiastic researcher
working on new methods for 3d computer vision workflows and methods.
The position is embedded into the interdisciplinary subproject Portable
and Adaptive Data Analysis Workflows for Real-Time 3D Vision, which is
processed jointly between Computer Science and Physics and also in
collaboration with the Computer Vision & Graphics group of Fraunhofer HHI.
- Full PhD position (first contract until until 06/2024) (salary EG 13,
about 48k Euros)
- development of novel 3D computer vision methods for microscopy, 3d
reconstruction/tracking workflow optimization for distributed computing
- send you application (quoting DR/089/22) to eisert@informatik.hu-berlin.de
- deadline July 27th, 2022
Requirements: Completed university degree in computer science or related
disciplines (preferably with very good marks); profound knowledge in
computer vision, deep learning, 3D image analysis, software engineering,
C++; experience in workflow systems beneficial; very good command of
English; team player
Within this project, we plan to establish an abstract denoscription of
common components of 3D vision data analysis workflows (DAWs) that
allows for an efficient distribution on different computing hardware
infrastructure as well as a simple adaptation to different experimental
settings and sensors. The work includes the analysis, modularization and
optimization of of 3d vision algorithms with respect to computational
and memory demands, scalability, data dependencies, and adaptability.
The focus will be on 3D vision / 3D reconstruction DAWs in the area of
microscopy and suitable schemes of parallelization, namely optical
reflection tomography of fossils captured in amber on a microscopic
scale and real time tracking.
More information about the position can be found at
https://www.informatik.hu-berlin.de/de/forschung/gebiete/viscom/open-research-position-fonda
🔭 @DeepGravity
Real-Time 3D Vision for Microscopy
https://www.informatik.hu-berlin.de/de/forschung/gebiete/viscom/open-research-position-fonda
Within the Collaborative Research Center Fonda, the Visual Computing
Group at Humboldt University is looking for an enthusiastic researcher
working on new methods for 3d computer vision workflows and methods.
The position is embedded into the interdisciplinary subproject Portable
and Adaptive Data Analysis Workflows for Real-Time 3D Vision, which is
processed jointly between Computer Science and Physics and also in
collaboration with the Computer Vision & Graphics group of Fraunhofer HHI.
- Full PhD position (first contract until until 06/2024) (salary EG 13,
about 48k Euros)
- development of novel 3D computer vision methods for microscopy, 3d
reconstruction/tracking workflow optimization for distributed computing
- send you application (quoting DR/089/22) to eisert@informatik.hu-berlin.de
- deadline July 27th, 2022
Requirements: Completed university degree in computer science or related
disciplines (preferably with very good marks); profound knowledge in
computer vision, deep learning, 3D image analysis, software engineering,
C++; experience in workflow systems beneficial; very good command of
English; team player
Within this project, we plan to establish an abstract denoscription of
common components of 3D vision data analysis workflows (DAWs) that
allows for an efficient distribution on different computing hardware
infrastructure as well as a simple adaptation to different experimental
settings and sensors. The work includes the analysis, modularization and
optimization of of 3d vision algorithms with respect to computational
and memory demands, scalability, data dependencies, and adaptability.
The focus will be on 3D vision / 3D reconstruction DAWs in the area of
microscopy and suitable schemes of parallelization, namely optical
reflection tomography of fossils captured in amber on a microscopic
scale and real time tracking.
More information about the position can be found at
https://www.informatik.hu-berlin.de/de/forschung/gebiete/viscom/open-research-position-fonda
🔭 @DeepGravity
Institut für Informatik
Open Research Position FONDA
PhD position in Multiple-view reconstruction of deformable objects
The Imagine team at LIRIS laboratory, Lyon- France is looking for a PhD student to work on deformable 3D reconstruction from multiple views (Link to offer). The goal of this project is to develop fast reconstruction algorithms.
The PhD will be supervised by Prof. Liming Chen (liming.chen@ec-lyon.fr) and Shaifali Parashar (shaifali.parashar@liris.cnrs.fr) .
Requirements:
Masters in computer vision, robotics, machine learning, mathematics or any field related to the topic
Strong programming skills in C++ and python
Fluency in English
Project duration: 36 months
Tentative start date: October 2022
How to apply:
Please send your CV, trannoscripts and 2 reference letters to Liming Chen and Shaifali Parashar with the subject "Multiple-view reconstruction of deformable objects ".
Best,
Shaifali
🔭 @DeepGravity
The Imagine team at LIRIS laboratory, Lyon- France is looking for a PhD student to work on deformable 3D reconstruction from multiple views (Link to offer). The goal of this project is to develop fast reconstruction algorithms.
The PhD will be supervised by Prof. Liming Chen (liming.chen@ec-lyon.fr) and Shaifali Parashar (shaifali.parashar@liris.cnrs.fr) .
Requirements:
Masters in computer vision, robotics, machine learning, mathematics or any field related to the topic
Strong programming skills in C++ and python
Fluency in English
Project duration: 36 months
Tentative start date: October 2022
How to apply:
Please send your CV, trannoscripts and 2 reference letters to Liming Chen and Shaifali Parashar with the subject "Multiple-view reconstruction of deformable objects ".
Best,
Shaifali
🔭 @DeepGravity
PostDoc or full time research position for Robot Learning at TCS Research India
Dear All,
Our research team in TCS research India is looking for motivated Postdoc or full time doctorate candidates with good publications to work on topic related to Robot Learning where the aim is to endow a robot with higher level of cognition so that they can physically sense the world and interact with their environment in the realm of embodied artificial intelligence.
In particular, we aim to build housekeeping robots for tyding up a room/facility along with humans. This setting integrates a number of the central challenges of artificial intelligence (AI) research: complex visual perception including combination of touch and vision, goal-directed planning, manipulation and physical motion, grounded language comprehension and production, and human-robot social interaction/navigation/collaboration in an open world.
Who can apply?:
Post-doc of full time: Recent Computer Science or AI based Robotics Ph.D. candidates who have submitted their thesis or very near to it in the relevant areas of cognitive robotics.
We are looking for candidates with some of the following skills or equivalent to these:
Domain Skills:
Computer Vision: 3D Reconstruction, point cloud registration, pose estimation, visual odometry etc.
Robotics: Path planning, motion planning, navigation, exploration, grasping methods
Deep Learning: Hands-on experience in reinforcement learning or Self-supervised learning, and graph neural networks.
Technical Skills:
Coding Language: Python (Primary), C++ (Basic), familiarity on ROS, Pybullet or any other simulation environment like Habitat/iGibson
Deep Learning Framework: PyTorch (Primary), Tensorflow (Basic)
Good interpersonal skills to communicate ideas, experimental results, and analysis with other team members.
Interested candidates can send their CV with the information that shows the required domain and technical skills along with publication details (These are important in the selection process).
Send CVs to b.bhowmick@tcs.com with the subject line “Research Opportunities at Cognitive Robotics, TCS Research”.
For any query, you may write to the following.
Dr. Brojeshwar Bhowmick, Senior Scientist, TCS Research ( b.bhowmick@tcs.com)
Best Regards,
Brojeshwar
____________________________________________
Dr. Brojeshwar Bhowmick,
Senior Scientist,
TCS Research
Cell:- 7044944788
Mailto: b.bhowmick@tcs.com
Website: https://sites.google.com/view/brojeshwar/home
🔭 @DeepGravity
Dear All,
Our research team in TCS research India is looking for motivated Postdoc or full time doctorate candidates with good publications to work on topic related to Robot Learning where the aim is to endow a robot with higher level of cognition so that they can physically sense the world and interact with their environment in the realm of embodied artificial intelligence.
In particular, we aim to build housekeeping robots for tyding up a room/facility along with humans. This setting integrates a number of the central challenges of artificial intelligence (AI) research: complex visual perception including combination of touch and vision, goal-directed planning, manipulation and physical motion, grounded language comprehension and production, and human-robot social interaction/navigation/collaboration in an open world.
Who can apply?:
Post-doc of full time: Recent Computer Science or AI based Robotics Ph.D. candidates who have submitted their thesis or very near to it in the relevant areas of cognitive robotics.
We are looking for candidates with some of the following skills or equivalent to these:
Domain Skills:
Computer Vision: 3D Reconstruction, point cloud registration, pose estimation, visual odometry etc.
Robotics: Path planning, motion planning, navigation, exploration, grasping methods
Deep Learning: Hands-on experience in reinforcement learning or Self-supervised learning, and graph neural networks.
Technical Skills:
Coding Language: Python (Primary), C++ (Basic), familiarity on ROS, Pybullet or any other simulation environment like Habitat/iGibson
Deep Learning Framework: PyTorch (Primary), Tensorflow (Basic)
Good interpersonal skills to communicate ideas, experimental results, and analysis with other team members.
Interested candidates can send their CV with the information that shows the required domain and technical skills along with publication details (These are important in the selection process).
Send CVs to b.bhowmick@tcs.com with the subject line “Research Opportunities at Cognitive Robotics, TCS Research”.
For any query, you may write to the following.
Dr. Brojeshwar Bhowmick, Senior Scientist, TCS Research ( b.bhowmick@tcs.com)
Best Regards,
Brojeshwar
____________________________________________
Dr. Brojeshwar Bhowmick,
Senior Scientist,
TCS Research
Cell:- 7044944788
Mailto: b.bhowmick@tcs.com
Website: https://sites.google.com/view/brojeshwar/home
🔭 @DeepGravity
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Dr. Brojeshwar Bhowmick is a senior scientist leading the research in the area of Visual Computing and Robot learning in TCS Research, Kolkata, India. Before that he was computer science engineer in the Avisere Technology Pvt. Ltd. which is now known as…
PhD Position: Computer Vision and Road Safety
Dear all,
We are recruiting for a three-year PhD position on computer vision, road safety, and data privacy at the Technical University of Denmark (DTU).
The position is based at the Transport Psychology Section and the Machine Learning for Smart Mobility Section of DTU, with a one year stay at Nanyang Technological University Singapore (NTU). The PhD will be conducted under the DTU-NTU Double Doctorate Degree agreement. The deadline for application is the 7th of September 2022 (Danish time).
You can contact me at felix@dtu.dk for more info on the position.
You can find more details below and under this application link:
https://www.dtu.dk/om-dtu/job-og-karriere/ledige-stillinger/job?id=d65debfd-8864-4824-adc5-d3253c7dbdb5
Best,
Felix
*Detailed Denoscription*
DTU Management’s Transport Division invites applications for a 3-year PhD position in the field of computer vision, edge computing, federated learning, and road safety. The successful candidate will join the Transport Psychology Group and will work under the supervision of Assistant Professor Felix Siebert, Senior Researcher Mette Møller, and Professor Francisco Pereira.
The PhD project will investigate privacy-preserving detection of safety-related behaviour of road users in the road environment, with computer vision and federated learning. Relevant data will be collected in road environments in Denmark and Singapore. State-of-the-art object detection approaches will be applied on the collected data. Detection robustness and privacy-preserving features, including edge computing and federated learning, will be developed. Collected behavioural data will be used to identify patterns of safe and unsafe behaviour of road users, within the scopes of short- and long-term trends.
The project is a strategic collaboration between the Technical University of Denmark (DTU) and its Alliance Network partner Nanyang Technological University (NTU) and will be conducted under the DTU-NTU double degree framework agreement which offers the opportunity to receive PhD diplomas from both DTU (home institution) and NTU (host institution). Your PhD study will include a 1-year stay at NTU.
You will be a member of the Transport Psychology section at the Department for Technology, Management and Economics (DTU Management) at the Technical University of Denmark. You will work under the supervision of Senior Researcher Mette Møller, Professor Francisco Pereira (Machine Learning for Smart Mobility section), and Assistant Professor Felix Siebert. Further supervision is provided by Professor Dusit Niyato from the School of Computer Science and Engineering (SCSE) at NTU.
Responsibilities and qualifications
Your primary tasks will be to
· Plan and conduct systematic roadside video data collection in Denmark and Singapore
· Based on the collected data, develop, test, and apply object detection approaches for safety related behaviour
· Advance the state of the art in edge computing and/or federated learning to facilitate data privacy
· Analyse the collected road user data for behavioural patterns
· Write academic papers aimed at high-impact journals
· Participate in international conferences and workshops
· Disseminate research results and teach as part of the overall PhD education
You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. Specifically, we seek applicants with a master's degree in transport, mathematics, statistics, computer science, civil engineering, industrial engineering, or a related discipline.
We are looking for an ambitious, self-organized individual with strong project management and communication skills. Applicants should have experience in some of the following areas: computer vision, federated learning, edge computing, statistics, machine learning, data collection, and analysis. Programming skills in Python or similar and proficient English language skills are also required.
Dear all,
We are recruiting for a three-year PhD position on computer vision, road safety, and data privacy at the Technical University of Denmark (DTU).
The position is based at the Transport Psychology Section and the Machine Learning for Smart Mobility Section of DTU, with a one year stay at Nanyang Technological University Singapore (NTU). The PhD will be conducted under the DTU-NTU Double Doctorate Degree agreement. The deadline for application is the 7th of September 2022 (Danish time).
You can contact me at felix@dtu.dk for more info on the position.
You can find more details below and under this application link:
https://www.dtu.dk/om-dtu/job-og-karriere/ledige-stillinger/job?id=d65debfd-8864-4824-adc5-d3253c7dbdb5
Best,
Felix
*Detailed Denoscription*
DTU Management’s Transport Division invites applications for a 3-year PhD position in the field of computer vision, edge computing, federated learning, and road safety. The successful candidate will join the Transport Psychology Group and will work under the supervision of Assistant Professor Felix Siebert, Senior Researcher Mette Møller, and Professor Francisco Pereira.
The PhD project will investigate privacy-preserving detection of safety-related behaviour of road users in the road environment, with computer vision and federated learning. Relevant data will be collected in road environments in Denmark and Singapore. State-of-the-art object detection approaches will be applied on the collected data. Detection robustness and privacy-preserving features, including edge computing and federated learning, will be developed. Collected behavioural data will be used to identify patterns of safe and unsafe behaviour of road users, within the scopes of short- and long-term trends.
The project is a strategic collaboration between the Technical University of Denmark (DTU) and its Alliance Network partner Nanyang Technological University (NTU) and will be conducted under the DTU-NTU double degree framework agreement which offers the opportunity to receive PhD diplomas from both DTU (home institution) and NTU (host institution). Your PhD study will include a 1-year stay at NTU.
You will be a member of the Transport Psychology section at the Department for Technology, Management and Economics (DTU Management) at the Technical University of Denmark. You will work under the supervision of Senior Researcher Mette Møller, Professor Francisco Pereira (Machine Learning for Smart Mobility section), and Assistant Professor Felix Siebert. Further supervision is provided by Professor Dusit Niyato from the School of Computer Science and Engineering (SCSE) at NTU.
Responsibilities and qualifications
Your primary tasks will be to
· Plan and conduct systematic roadside video data collection in Denmark and Singapore
· Based on the collected data, develop, test, and apply object detection approaches for safety related behaviour
· Advance the state of the art in edge computing and/or federated learning to facilitate data privacy
· Analyse the collected road user data for behavioural patterns
· Write academic papers aimed at high-impact journals
· Participate in international conferences and workshops
· Disseminate research results and teach as part of the overall PhD education
You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. Specifically, we seek applicants with a master's degree in transport, mathematics, statistics, computer science, civil engineering, industrial engineering, or a related discipline.
We are looking for an ambitious, self-organized individual with strong project management and communication skills. Applicants should have experience in some of the following areas: computer vision, federated learning, edge computing, statistics, machine learning, data collection, and analysis. Programming skills in Python or similar and proficient English language skills are also required.
https://www.dtu.dk
Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.
Assessment
The review of applications will begin on 8 September 2022.
We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.
Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years. The preferred starting date is 1 January 2023. The position is a full-time position.
You can read more about career paths at DTU here.
Workplace
This PhD study is under the Double Doctorate Degree agreement between DTU and NTU. DTU will be the home institution that will handle all the administrative and financial aspects of the joint education. DTU will enrol the candidate in one of its PhD programs and nominate the main supervisor. NTU will be the host institution and will also enrol the candidate in one of its PhD programs. The candidate must spend a minimum of one year at each of the two institutions.
Further information
Further information may be obtained from Assistant Professor Felix Siebert (felix@dtu.dk).
You can read more about DTU Management at www.man.dtu.dk/english.
If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.
Application procedure
Your complete online application must be submitted no later than 7 September 2022 (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:
A letter motivating the application (cover letter)
Curriculum vitae
Grade trannoscripts and BSc/MSc diploma (in English) including official denoscription of grading scale
You may apply prior to obtaining your master's degree but cannot begin before having received it.
Applications received after the deadline will not be considered.
All interested candidates irrespective of age, gender, race, disability, religion, or ethnic background are encouraged to apply.
About the department
The Transport Psychology section and the Machine Learning for Smart Mobility section belong to the Transport division of the Department of Technology, Management and Economics (DTU Management) at DTU. The division conducts research and teaching in the field of traffic and transport planning, with particular focus on road user behaviour modelling and analysis, machine learning, and simulation.
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules for the PhD education.
Assessment
The review of applications will begin on 8 September 2022.
We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.
Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years. The preferred starting date is 1 January 2023. The position is a full-time position.
You can read more about career paths at DTU here.
Workplace
This PhD study is under the Double Doctorate Degree agreement between DTU and NTU. DTU will be the home institution that will handle all the administrative and financial aspects of the joint education. DTU will enrol the candidate in one of its PhD programs and nominate the main supervisor. NTU will be the host institution and will also enrol the candidate in one of its PhD programs. The candidate must spend a minimum of one year at each of the two institutions.
Further information
Further information may be obtained from Assistant Professor Felix Siebert (felix@dtu.dk).
You can read more about DTU Management at www.man.dtu.dk/english.
If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.
Application procedure
Your complete online application must be submitted no later than 7 September 2022 (Danish time). Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link "Apply online", fill out the online application form, and attach all your materials in English in one PDF file. The file must include:
A letter motivating the application (cover letter)
Curriculum vitae
Grade trannoscripts and BSc/MSc diploma (in English) including official denoscription of grading scale
You may apply prior to obtaining your master's degree but cannot begin before having received it.
Applications received after the deadline will not be considered.
All interested candidates irrespective of age, gender, race, disability, religion, or ethnic background are encouraged to apply.
About the department
The Transport Psychology section and the Machine Learning for Smart Mobility section belong to the Transport division of the Department of Technology, Management and Economics (DTU Management) at DTU. The division conducts research and teaching in the field of traffic and transport planning, with particular focus on road user behaviour modelling and analysis, machine learning, and simulation.
DTU Management conducts high-level research and teaching with a focus on sustainability, transport, innovation, and management science. Our goal is to create knowledge on the societal aspects of technology - including the interaction between technology and sustainability, business growth, infrastructure, and prosperity. Therefore, we explore and create value in the areas of management science, innovation and design thinking, business analytics, systems and risk analyses, human behaviour, regulation, and policy analysis. The department offers teaching from introductory to advanced courses/projects at BSc, MSc, and PhD level. The Department has a staff of approximately 350 people.
Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 13,400 students and 5,800 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.
Felix Wilhelm Siebert
Assistant Professor
Division of Transport
Transport Psychology Section
felix@dtu.dk
Bygningstorvet
Building 116
2800 Kgs. Lyngby
Technical University of Denmark
🔭 @DeepGravity
Technology for people
DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to solve the global challenges formulated in the UN’s 17 Sustainable Development Goals. Hans Christian Ørsted founded DTU in 1829 with a clear vision to develop and create value using science and engineering to benefit society. That vision lives on today. DTU has 13,400 students and 5,800 employees. We work in an international atmosphere and have an inclusive, evolving, and informal working environment. DTU has campuses in all parts of Denmark and in Greenland, and we collaborate with the best universities around the world.
Felix Wilhelm Siebert
Assistant Professor
Division of Transport
Transport Psychology Section
felix@dtu.dk
Bygningstorvet
Building 116
2800 Kgs. Lyngby
Technical University of Denmark
🔭 @DeepGravity
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𝗪𝗵𝗲𝗿𝗲 𝗶𝘀 𝗚𝗲𝗿𝗺𝗮𝗻 𝗔𝗜 𝘁𝗮𝗹𝗲𝗻𝘁 𝗰𝗼𝗺𝗶𝗻𝗴 𝗳𝗿𝗼𝗺… | Jannik Wiedenhaupt | 143 comments
𝗪𝗵𝗲𝗿𝗲 𝗶𝘀 𝗚𝗲𝗿𝗺𝗮𝗻 𝗔𝗜 𝘁𝗮𝗹𝗲𝗻𝘁 𝗰𝗼𝗺𝗶𝗻𝗴 𝗳𝗿𝗼𝗺 𝗮𝗻𝗱 𝗴𝗼𝗶𝗻𝗴?
Germany has an amazing education system and great (almost free) technical universities, so I was wondering how well they do in attracting AI research talent and keeping it.
On of my recent posts Pegah Maham…
Germany has an amazing education system and great (almost free) technical universities, so I was wondering how well they do in attracting AI research talent and keeping it.
On of my recent posts Pegah Maham…