#PhD position
Title: PhD position in Trustworthy ML.
> Denoscription: We are hiring PhD students, with strong background in statistics, algorithms and theory of ML. Data privacy and trustworthy machine learning..
> National University of Singapore, Singapore.
🌐 https://twitter.com/rzshokri/status/1320560163930058752?s=19
🆔 @PositionClub
Title: PhD position in Trustworthy ML.
> Denoscription: We are hiring PhD students, with strong background in statistics, algorithms and theory of ML. Data privacy and trustworthy machine learning..
> National University of Singapore, Singapore.
🌐 https://twitter.com/rzshokri/status/1320560163930058752?s=19
🆔 @PositionClub
Twitter
Reza Shokri
We are hiring PhD students, with strong background in statistics, algorithms and theory of ML. Data privacy and trustworthy machine learning. https://t.co/PuAyE8TmMb
#PhD position
Title: PhD Positions in Computational and Theoretical Neuroscience and Machine Learning.
> Denoscription: The PhD programme lasts four years, including the first year of intensive instruction in techniques and research in theoretical and systems neuroscience and machine learning. Courses in the first year, taught in conjunction with colleagues from the SWC and CSML, provide a comprehensive introduction to theoretical and systems neuroscience and to machine learning; with further multidisciplinary training in other areas of neuroscience also available. Students are encouraged to work and interact closely with peers and faculty in the SWC and CSML throughout their PhD, providing a uniquely multidisciplinary research environment. Projects involving collaboration within or outside UCL are welcome. For more information see our programme structure.
Students at the Gatsby Unit study toward a PhD in either machine learning or computational and theoretical neuroscience, with minor emphasis in the complementary field. Exceptionally, some students with pre-secured shorter-term studentships have joined us to study for an MPhil degree in one of these fields. Besides these Gatsby-funded programmes, students from other PhD programmes are also able to carry out all or part of their research in Unit. We do not offer undergraduate or taught masters programmes, nor a research masters, however students in some UCL Masters programmes may carry out projects in the Unit.
Applicants to the Gatsby PhD programme should have a strong analytical and mathematical background, a keen interest in neuroscience and/or machine learning and a relevant first degree, for example in Computer Science, Engineering, Mathematics, Neuroscience, Physics, Psychology or Statistics.
Full funding is available to all students, regardless of nationality. Gatsby PhD studentships cover the cost of tuition at the appropriate rate, and include a tax-free stipend, presently £24,000 per annum. The Unit also welcomes applications from students with pre-secured funding or who are currently soliciting other scholarship/studentships.
> Dept: Gatsby Unit
> University College London, UK.
💯Deadline: 15 Nov 2020
🌐 https://www.ucl.ac.uk/gatsby/study-and-work/phd-programme
🆔 @PositionClub
Title: PhD Positions in Computational and Theoretical Neuroscience and Machine Learning.
> Denoscription: The PhD programme lasts four years, including the first year of intensive instruction in techniques and research in theoretical and systems neuroscience and machine learning. Courses in the first year, taught in conjunction with colleagues from the SWC and CSML, provide a comprehensive introduction to theoretical and systems neuroscience and to machine learning; with further multidisciplinary training in other areas of neuroscience also available. Students are encouraged to work and interact closely with peers and faculty in the SWC and CSML throughout their PhD, providing a uniquely multidisciplinary research environment. Projects involving collaboration within or outside UCL are welcome. For more information see our programme structure.
Students at the Gatsby Unit study toward a PhD in either machine learning or computational and theoretical neuroscience, with minor emphasis in the complementary field. Exceptionally, some students with pre-secured shorter-term studentships have joined us to study for an MPhil degree in one of these fields. Besides these Gatsby-funded programmes, students from other PhD programmes are also able to carry out all or part of their research in Unit. We do not offer undergraduate or taught masters programmes, nor a research masters, however students in some UCL Masters programmes may carry out projects in the Unit.
Applicants to the Gatsby PhD programme should have a strong analytical and mathematical background, a keen interest in neuroscience and/or machine learning and a relevant first degree, for example in Computer Science, Engineering, Mathematics, Neuroscience, Physics, Psychology or Statistics.
Full funding is available to all students, regardless of nationality. Gatsby PhD studentships cover the cost of tuition at the appropriate rate, and include a tax-free stipend, presently £24,000 per annum. The Unit also welcomes applications from students with pre-secured funding or who are currently soliciting other scholarship/studentships.
> Dept: Gatsby Unit
> University College London, UK.
💯Deadline: 15 Nov 2020
🌐 https://www.ucl.ac.uk/gatsby/study-and-work/phd-programme
🆔 @PositionClub
Gatsby Computational Neuroscience Unit
PhD programme
#PhD position
Title: PhD in Machine Learning for Healthcare.
> Denoscription:
We have a handful of fully-funded positions for PhD students to develop cutting-edge machine learning methods for healthcare. If you're interested, get in touch.
> Cambridge, UK.
🌐 https://twitter.com/MihaelaVDS/status/1320719425461506049?s=19
🆔 @PositionClub
Title: PhD in Machine Learning for Healthcare.
> Denoscription:
We have a handful of fully-funded positions for PhD students to develop cutting-edge machine learning methods for healthcare. If you're interested, get in touch.
> Cambridge, UK.
🌐 https://twitter.com/MihaelaVDS/status/1320719425461506049?s=19
🆔 @PositionClub
Twitter
Mihaela van der Schaar
🚨 OPPORTUNITY ALERT! We have a handful of fully-funded positions for PhD students to develop cutting-edge machine learning methods for healthcare. If you're interested, get in touch; if you know someone who might be interested, please share this! 👇🏼 http…
Postdoc position
Title: Postdoc in Physics-Guided Learning for Spatiotemporal Decision Making.
> Denoscription: We seek exceptional postdoctoral candidates hosted at UCSD Computer Science & Engineering by Prof. Rose Yu . The initial term of these positions is one year with the possiblity for renewal. The target start date is early 2021 but is flexible.
Background
The recent breakthroughs in Artificial Intelligence (AI) and Machine Learning (ML) demonstrate new promises for decision making in complex spatiotemporal environments. Unfortunately, a key challenge to deploy ML in real-world is the large amount of labeled training data required to train complex deep learning models. We will develop sample efficient physics-guided machine learning to learn from spatiotemporal data such as trajectories and videos. The goal is to learn complex spatiotemporal dynamics in various real-world scenarios, including autonomous vehicle tracking and navigation, multi-agent team behavior modeling, and atmospheric turbulence simulation.
Qualifications
Ph.D. in computer science, physics, mathematics, engineering or other related fields.
Strong interests in both theory and application of machine learning, especially spatiotemporal reasoning.
Prior experience working with large-scale data set.
Paper in ICML, NeurIPS, KDD, ICLR is a plus.
Communication, presentation, writing, and teamwork skills..
> Dept: Computer Science
> UCSD, US.
🌐 http://roseyu.com/postdoc.html
🆔 @PositionClub
Title: Postdoc in Physics-Guided Learning for Spatiotemporal Decision Making.
> Denoscription: We seek exceptional postdoctoral candidates hosted at UCSD Computer Science & Engineering by Prof. Rose Yu . The initial term of these positions is one year with the possiblity for renewal. The target start date is early 2021 but is flexible.
Background
The recent breakthroughs in Artificial Intelligence (AI) and Machine Learning (ML) demonstrate new promises for decision making in complex spatiotemporal environments. Unfortunately, a key challenge to deploy ML in real-world is the large amount of labeled training data required to train complex deep learning models. We will develop sample efficient physics-guided machine learning to learn from spatiotemporal data such as trajectories and videos. The goal is to learn complex spatiotemporal dynamics in various real-world scenarios, including autonomous vehicle tracking and navigation, multi-agent team behavior modeling, and atmospheric turbulence simulation.
Qualifications
Ph.D. in computer science, physics, mathematics, engineering or other related fields.
Strong interests in both theory and application of machine learning, especially spatiotemporal reasoning.
Prior experience working with large-scale data set.
Paper in ICML, NeurIPS, KDD, ICLR is a plus.
Communication, presentation, writing, and teamwork skills..
> Dept: Computer Science
> UCSD, US.
🌐 http://roseyu.com/postdoc.html
🆔 @PositionClub
👍1
#PhD position
Title: PhD in Machine Learning and Embedded Systems.
> Denoscription: I am looking for multiple self-motivated Ph.D. students to join my group at UC Irvine for Fall 2021. The areas of interest are: machine learning (theory and application), software-hardware co-design, embedded systems, and computer architecture. All candidates are expected to have excellent programming skills.
If you are interested, please email me a copy of your CV: m.imani@uci.edu. Please use "Ph.D. Application Fall 2021" as the noscript of your email..
> UC Irvine, US.
🌐 https://www.linkedin.com/posts/mohsen-imani-3491164b_university-of-california-irvine-activity-6726738091475922944-olAY
🆔 @PositionClub
Title: PhD in Machine Learning and Embedded Systems.
> Denoscription: I am looking for multiple self-motivated Ph.D. students to join my group at UC Irvine for Fall 2021. The areas of interest are: machine learning (theory and application), software-hardware co-design, embedded systems, and computer architecture. All candidates are expected to have excellent programming skills.
If you are interested, please email me a copy of your CV: m.imani@uci.edu. Please use "Ph.D. Application Fall 2021" as the noscript of your email..
> UC Irvine, US.
🌐 https://www.linkedin.com/posts/mohsen-imani-3491164b_university-of-california-irvine-activity-6726738091475922944-olAY
🆔 @PositionClub
Linkedin
Mohsen Imani on LinkedIn: University of California, Irvine | 11 comments
I am looking for multiple self-motivated Ph.D. students to join my group at UC Irvine for Fall 2021. The areas of interest are: machine learning (theory and… | 11 comments on LinkedIn
#Master scholarship
Mälardalen University scholarship programme
Sweden
https://www.mdh.se/international/application-and-admission/malardalen-university-scholarship-programme
🆔 @positionclub
Mälardalen University scholarship programme
Sweden
https://www.mdh.se/international/application-and-admission/malardalen-university-scholarship-programme
🆔 @positionclub
#PhD position
Title: PhD position in Machine and Reinforcement Learning.
> Denoscription: The Uncertainty in Artificial Intelligence (UAI) group is a new and quickly growing group embedded in the Data and AI (DAI) cluster at the Eindhoven University of Technology. In the DAI cluster, we aim at developing foundations of AI for the present and the future. This includes the design of new AI methods, development of AI algorithms and tools with a view at expanding the reach of AI and its generalization abilities. In particular, we study foundational issues of robustness, safety, trust, reliability, tractability, scalability, interpretability and explain ability of AI.
The UAI group is looking for a highly motivated and skilled PhD candidate to work in an area of Machine Learning as suggested below. The concrete research direction will be determined together with the successful candidate. Potential topics include, but are not restricted to:
(Deep) Reinforcement Learning
(Contextual) Multi-Armed Bandits
Counterfactual Learning
Fairness-aware Learning
Fairness in Reinforcement Learning
Off-policy Reinforcement Learning
Modeling Bias in Machine Learning
Decision Making under Uncertainty
Auto ML
Explainable AI
Recommendation Systems
We encourage you to express your preferences on the above topics (if applicable) in your research statement.
Functie-eisen
We are looking for a motivated candidate with:
Master’s degree in Computer Science, Mathematics, or a related field;
Excellent analytical skills;
Excellent coding skills (e.g. Python, PyTorch, Tensorflow);
Excellent academic writing and presentation skills;
Proficiency in English (written and spoken);
Desire to conduct excellent research and publish in high quality conferences and journals;
Independent thinker and self-responsibility;
Ability and desire to collaborate and work in teams;
Ability and desire to support teaching and to co-supervise bachelor and master students;
Knowledge of Reinforcement Learning is an advantage..
> Dept: Information
> TU Eindhoven, Netherlands.
🌐
💯 Deadline: ASAP https://jobs.tue.nl/nl/vacature/phd-position-in-machine-learning-864922.html
🆔 @PositionClub
Title: PhD position in Machine and Reinforcement Learning.
> Denoscription: The Uncertainty in Artificial Intelligence (UAI) group is a new and quickly growing group embedded in the Data and AI (DAI) cluster at the Eindhoven University of Technology. In the DAI cluster, we aim at developing foundations of AI for the present and the future. This includes the design of new AI methods, development of AI algorithms and tools with a view at expanding the reach of AI and its generalization abilities. In particular, we study foundational issues of robustness, safety, trust, reliability, tractability, scalability, interpretability and explain ability of AI.
The UAI group is looking for a highly motivated and skilled PhD candidate to work in an area of Machine Learning as suggested below. The concrete research direction will be determined together with the successful candidate. Potential topics include, but are not restricted to:
(Deep) Reinforcement Learning
(Contextual) Multi-Armed Bandits
Counterfactual Learning
Fairness-aware Learning
Fairness in Reinforcement Learning
Off-policy Reinforcement Learning
Modeling Bias in Machine Learning
Decision Making under Uncertainty
Auto ML
Explainable AI
Recommendation Systems
We encourage you to express your preferences on the above topics (if applicable) in your research statement.
Functie-eisen
We are looking for a motivated candidate with:
Master’s degree in Computer Science, Mathematics, or a related field;
Excellent analytical skills;
Excellent coding skills (e.g. Python, PyTorch, Tensorflow);
Excellent academic writing and presentation skills;
Proficiency in English (written and spoken);
Desire to conduct excellent research and publish in high quality conferences and journals;
Independent thinker and self-responsibility;
Ability and desire to collaborate and work in teams;
Ability and desire to support teaching and to co-supervise bachelor and master students;
Knowledge of Reinforcement Learning is an advantage..
> Dept: Information
> TU Eindhoven, Netherlands.
🌐
💯 Deadline: ASAP https://jobs.tue.nl/nl/vacature/phd-position-in-machine-learning-864922.html
🆔 @PositionClub
jobs.tue.nl
This job is unavailable
De TU/e is voortdurend op zoek naar wetenschappelijk en niet-wetenschappelijk personeel om haar ambities waar te maken. Kijk hier voor ons actuele vacatureaanbod.
#PhD position
Title: PhD – Hybrid (AI-driven and physics based) Models for Dynamical Systems.
> Denoscription: Hybrid modeling of a dynamical system leverages prior domain knowledge in guiding data-driven machine learning towards more informed, explainable predictive models. While model-based simulations aim at modeling stable causal and physical relationships and machine learning excels in mining hidden patterns in measurements, hybrid modeling tries to harness the best of both approaches.
In this PhD project, the objective is to develop an automated framework for hybrid model generation, training and evaluation. An important decision in this framework is the selection of the most appropriate hybridization paradigm (accompanied with its proper training method) for a given task. For this purpose, careful design of well-defined selection criteria is required for targeting an intuitive guideline for model selection. Additionally, superior performance of selected models need to be validated not only on attainable real-world measurements but also as to which extend physical constraints have been satisfied. During your PhD, you will be part of the active research team at the Bosch Center for Artificial Intelligence (BCAI).
Right from day one, you will invent novel approaches for model hybridization.You will conduct prototypical implementations and benchmarking on both synthetic scenarios and real-world data sets.Furthermore, you publish in top-tier conferences (ICML, NIPS, ICLR, AISTATS etc.) and journals (JMLR, PAMI etc.).You screen literature and build up close contact with the academic community.Be part of the team and participate in academic interactions within the BCAI research team and have the chance of integrating your developments in real industrial applications..
> Bosch Center for AI, Germany.
🌐 https://jobs.smartrecruiters.com/BoschGroup/743999722884815-phd-hybrid-ai-driven-and-physics-based-models-for-dynamical-systems
🆔 @PositionClub
Title: PhD – Hybrid (AI-driven and physics based) Models for Dynamical Systems.
> Denoscription: Hybrid modeling of a dynamical system leverages prior domain knowledge in guiding data-driven machine learning towards more informed, explainable predictive models. While model-based simulations aim at modeling stable causal and physical relationships and machine learning excels in mining hidden patterns in measurements, hybrid modeling tries to harness the best of both approaches.
In this PhD project, the objective is to develop an automated framework for hybrid model generation, training and evaluation. An important decision in this framework is the selection of the most appropriate hybridization paradigm (accompanied with its proper training method) for a given task. For this purpose, careful design of well-defined selection criteria is required for targeting an intuitive guideline for model selection. Additionally, superior performance of selected models need to be validated not only on attainable real-world measurements but also as to which extend physical constraints have been satisfied. During your PhD, you will be part of the active research team at the Bosch Center for Artificial Intelligence (BCAI).
Right from day one, you will invent novel approaches for model hybridization.You will conduct prototypical implementations and benchmarking on both synthetic scenarios and real-world data sets.Furthermore, you publish in top-tier conferences (ICML, NIPS, ICLR, AISTATS etc.) and journals (JMLR, PAMI etc.).You screen literature and build up close contact with the academic community.Be part of the team and participate in academic interactions within the BCAI research team and have the chance of integrating your developments in real industrial applications..
> Bosch Center for AI, Germany.
🌐 https://jobs.smartrecruiters.com/BoschGroup/743999722884815-phd-hybrid-ai-driven-and-physics-based-models-for-dynamical-systems
🆔 @PositionClub
#PhD position
Title: Multiple PhD positions in Computer Architecture with Machine Learning, Data Mining, and Bioinformatics.
> Denoscription: I am looking for multiple highly motivated PhD students interested in working at the intersection of computer architecture with machine learning, data mining, databases, and bioinformatics, to join my group at UC Riverside.
If you are interested, please fill out this form:
https://lnkd.in/g6S_KDq.
> UC Riverside, US.
🌐 https://www.linkedin.com/posts/elaheh-sadredini-phd-823002b2_google-forms-create-and-analyze-surveys-activity-6729125036382408704-_1r7
🆔 @PositionClub
Title: Multiple PhD positions in Computer Architecture with Machine Learning, Data Mining, and Bioinformatics.
> Denoscription: I am looking for multiple highly motivated PhD students interested in working at the intersection of computer architecture with machine learning, data mining, databases, and bioinformatics, to join my group at UC Riverside.
If you are interested, please fill out this form:
https://lnkd.in/g6S_KDq.
> UC Riverside, US.
🌐 https://www.linkedin.com/posts/elaheh-sadredini-phd-823002b2_google-forms-create-and-analyze-surveys-activity-6729125036382408704-_1r7
🆔 @PositionClub
Linkedin
Elaheh Sadredini, PhD on LinkedIn: #phd #computerarchitecture #deeplearning #accelerators #bigdataprocessing | 19 comments
I am looking for multiple highly motivated PhD students interested in working at the intersection of computer architecture with machine learning, data mining… | 19 comments on LinkedIn
#PhD & #PostDoc Positions
> Swiss Federal Laboratories for Materials Science and Technology (Empa)
> Switzerland
🌐 https://apply.refline.ch/673276/search.html?lang=en
🙏 Thanks to "Amin"
🆔 @PositionClub
> Swiss Federal Laboratories for Materials Science and Technology (Empa)
> Switzerland
🌐 https://apply.refline.ch/673276/search.html?lang=en
🙏 Thanks to "Amin"
🆔 @PositionClub
#MSc / #PhD Position
Topic: Medical Physics & Machine Learning
> University of British Columbia, Canada
🆔 @PositionClub
Topic: Medical Physics & Machine Learning
> University of British Columbia, Canada
🆔 @PositionClub
#PhD & #PostDoc Positions
Topic: Decision support for grid operators
> EnergyVille & Dept. Electrical Eng. at KU Leuven, Belgium
💯 Deadline: 31 July 2020
🌐 https://www.energyville.be/jobs/phd-decision-support-grid-operators
🌐 https://www.energyville.be/jobs/postdoctoral-researcher-decision-support-grid-operators
🙏 Thanks to "Amin"
🆔 @PositionClub
Topic: Decision support for grid operators
> EnergyVille & Dept. Electrical Eng. at KU Leuven, Belgium
💯 Deadline: 31 July 2020
🌐 https://www.energyville.be/jobs/phd-decision-support-grid-operators
🌐 https://www.energyville.be/jobs/postdoctoral-researcher-decision-support-grid-operators
🙏 Thanks to "Amin"
🆔 @PositionClub
7 #PhD and 4 #PostDoc Positions
Topics: Cross-disciplinary research in AI
> Science of Intelligence Berlin - Cluster of Excellence, Germany
💯 Deadline: 20 November 2020
🌐 https://www.scienceofintelligence.de/call-for-applications/open-positions
🆔 @PositionClub
Topics: Cross-disciplinary research in AI
> Science of Intelligence Berlin - Cluster of Excellence, Germany
💯 Deadline: 20 November 2020
🌐 https://www.scienceofintelligence.de/call-for-applications/open-positions
🆔 @PositionClub
NYU.pdf
57.1 KB
#PhD Positions
Potential Projects:
- Risk-aware electricity markets
- Energy justice in climate change adaptation
- Cybersecurity of electric power distribution
- Peer-to-peer electricity markets
- Resiliency of urban electricity vulnerable consumers during electricity supply
interruptions
> Smart Energy Research (SEARCH) Group
> Power Lab.
> Dept. ECE, New York University, USA
💯 NO GRE
🙏 Thanks to "Amin"
🆔 @PositionClub
Potential Projects:
- Risk-aware electricity markets
- Energy justice in climate change adaptation
- Cybersecurity of electric power distribution
- Peer-to-peer electricity markets
- Resiliency of urban electricity vulnerable consumers during electricity supply
interruptions
> Smart Energy Research (SEARCH) Group
> Power Lab.
> Dept. ECE, New York University, USA
💯 NO GRE
🙏 Thanks to "Amin"
🆔 @PositionClub
#MSc & #PhD Positions
> AI Powered IoT Lab
> Dept. Artificial Intelligence Convergence
> Pukyong National University (PKNU), Korea
💯 Deadline: 16 Nov 2020
🙏 Thanks to "Amin"
🆔 @PositionClub
> AI Powered IoT Lab
> Dept. Artificial Intelligence Convergence
> Pukyong National University (PKNU), Korea
💯 Deadline: 16 Nov 2020
🙏 Thanks to "Amin"
🆔 @PositionClub
#PhD #Postdoc position
Title: PhD or Postdoc position on Probabilistic Modeling in the Wild.
> Denoscription: Real world environments are often noisy, ambiguous, evolving, and subject to contamination. In turn, deploying intelligent systems in these environments often requires a probabilistic approach. Quantifying uncertainty can help the system handle the ‘messiness’ of the real world. The Amsterdam Machine Learning Lab is looking for a PhD student or a postdoctoral researcher to study principled methods for deploying probabilistic models in the wild. Examples of avenues of research include (but are not limited to): how to incorporate prior knowledge and constraints, how to learn under dynamic computational limitations, how to ensure the system is robust to data shift, and how to efficiently incorporate human oversight. Such issues are of crucial importance when building probabilistic systems in practice. The solutions will require deep engagement with both statistical methodology (e.g. Bayesian modeling) and engineering practice (e.g. probabilistic programming)..
> Dept: Informatics Institute
> University of Amsterdam (UvA), Netherlands.
💯Deadline: 04 Jan 2021
🌐 https://www.uva.nl/en/content/vacancies/2020/10/20-621-phd-or-postdoc-position-on-probabilistic-modeling-in-the-wild.html
🆔 @PositionClub
Title: PhD or Postdoc position on Probabilistic Modeling in the Wild.
> Denoscription: Real world environments are often noisy, ambiguous, evolving, and subject to contamination. In turn, deploying intelligent systems in these environments often requires a probabilistic approach. Quantifying uncertainty can help the system handle the ‘messiness’ of the real world. The Amsterdam Machine Learning Lab is looking for a PhD student or a postdoctoral researcher to study principled methods for deploying probabilistic models in the wild. Examples of avenues of research include (but are not limited to): how to incorporate prior knowledge and constraints, how to learn under dynamic computational limitations, how to ensure the system is robust to data shift, and how to efficiently incorporate human oversight. Such issues are of crucial importance when building probabilistic systems in practice. The solutions will require deep engagement with both statistical methodology (e.g. Bayesian modeling) and engineering practice (e.g. probabilistic programming)..
> Dept: Informatics Institute
> University of Amsterdam (UvA), Netherlands.
💯Deadline: 04 Jan 2021
🌐 https://www.uva.nl/en/content/vacancies/2020/10/20-621-phd-or-postdoc-position-on-probabilistic-modeling-in-the-wild.html
🆔 @PositionClub
1_5575644776079818757.pdf
687.4 KB
Funded research internship at EPFL
EPFL Excellence in Engineering Program offers an intensive research training opportunity to international students interested in research careers in any field of engineering, science and technology. Selected students will be joining a research group at EPFL for a period of 8 to 12 weeks during the summer months, and get to attend a series of group meetings and workshops given by researchers from EPFL and abroad. Housing and living expenses will be covered, and travel costs may also be covered as well. This program is open to bachelor's students in their 2nd year or later, and master's students. More details can be found on the program website.
https://eee.epfl.ch/
Thanks to "Alireza"
🆔 @positionclub
EPFL Excellence in Engineering Program offers an intensive research training opportunity to international students interested in research careers in any field of engineering, science and technology. Selected students will be joining a research group at EPFL for a period of 8 to 12 weeks during the summer months, and get to attend a series of group meetings and workshops given by researchers from EPFL and abroad. Housing and living expenses will be covered, and travel costs may also be covered as well. This program is open to bachelor's students in their 2nd year or later, and master's students. More details can be found on the program website.
https://eee.epfl.ch/
Thanks to "Alireza"
🆔 @positionclub
#PhD #Postdoc position
Title: 7 PhDs and 4 Postdocs in Machine Learning, AI, Robotics, Neuroscience, etc.
> Denoscription: Cross-disciplinary research in artificial intelligence, machine learning, control, robotics, computer vision, behavioral biology, cognitive science, psychology, educational science, neuroscience, and philosophy.
Starting dates: Summer / Fall 2021
Duration: 3 years
Salary level: TV-L 13, 100%
What are the principles of intelligence, shared by all forms of intelligence, no matter whether artificial or biological, whether robot, computer program, human, or animal?
And how can we apply these principles to create intelligent technology?
Answering these questions - in an ethically responsible way - is the central scientific objective of the Cluster of Excellence Science of Intelligence https://lnkd.in/dwRTpDa
The cluster welcomes applications from all disciplines that contribute to intelligence research.
To apply, please visit https://lnkd.in/dy2tAzh where details of the individual research projects are also available.
#research #science #intelligenceresearch.
> Dept: Science of Intelligence Chair
> Technische Universität Berlin, Germany.
💯Deadline: 20 Nov 2020
🌐
🆔 @PositionClub
Title: 7 PhDs and 4 Postdocs in Machine Learning, AI, Robotics, Neuroscience, etc.
> Denoscription: Cross-disciplinary research in artificial intelligence, machine learning, control, robotics, computer vision, behavioral biology, cognitive science, psychology, educational science, neuroscience, and philosophy.
Starting dates: Summer / Fall 2021
Duration: 3 years
Salary level: TV-L 13, 100%
What are the principles of intelligence, shared by all forms of intelligence, no matter whether artificial or biological, whether robot, computer program, human, or animal?
And how can we apply these principles to create intelligent technology?
Answering these questions - in an ethically responsible way - is the central scientific objective of the Cluster of Excellence Science of Intelligence https://lnkd.in/dwRTpDa
The cluster welcomes applications from all disciplines that contribute to intelligence research.
To apply, please visit https://lnkd.in/dy2tAzh where details of the individual research projects are also available.
#research #science #intelligenceresearch.
> Dept: Science of Intelligence Chair
> Technische Universität Berlin, Germany.
💯Deadline: 20 Nov 2020
🌐
🆔 @PositionClub
#PhD position
Title: PhD in Causal Inference for Machine Learning.
> Denoscription: I will be looking for motivated Ph.D. students to work on fundamental problems in causal inference and machine learning @PurdueECE starting Fall'21 . Please share with those who may be interested.
> Dept: ECE
> Purdue, US.
🌐 https://twitter.com/murat_kocaoglu_/status/1326545717905694721?s=09
🆔 @PositionClub
Title: PhD in Causal Inference for Machine Learning.
> Denoscription: I will be looking for motivated Ph.D. students to work on fundamental problems in causal inference and machine learning @PurdueECE starting Fall'21 . Please share with those who may be interested.
> Dept: ECE
> Purdue, US.
🌐 https://twitter.com/murat_kocaoglu_/status/1326545717905694721?s=09
🆔 @PositionClub
Twitter
Murat Kocaoglu
I will be looking for motivated Ph.D. students to work on fundamental problems in causal inference and machine learning @PurdueECE starting Fall'21. Please share with those who may be interested.
#PhD position
Title: PhD in Computer Architecture, IoT Systems, and Security.
> Denoscription: I’m looking for multiple PhD students who are interested in doing research at the intersection of computer architecture, embedded/IoT systems, and security. If you are interested, please visit my website (nsehat.bol.ucla.edu) to learn more about these positions, and contact me via email..
> Dept: ECE
> UCLA, US.
🌐 http://nsehat.bol.ucla.edu/
🆔 @PositionClub
Title: PhD in Computer Architecture, IoT Systems, and Security.
> Denoscription: I’m looking for multiple PhD students who are interested in doing research at the intersection of computer architecture, embedded/IoT systems, and security. If you are interested, please visit my website (nsehat.bol.ucla.edu) to learn more about these positions, and contact me via email..
> Dept: ECE
> UCLA, US.
🌐 http://nsehat.bol.ucla.edu/
🆔 @PositionClub
nsehat.bol.ucla.edu
Nader Sehatbakhsh - Personal Webpage
My personal webpage