PhD Opening in Human-guided Robotic Behavior Learning
The Unmanned Systems Lab at University of Texas at San Antonio has 1-2 fully funded PhD openings in the area of human-guided robotic behavior learning. The main research goal is to develop new human-guided reinforcement learning algorithms to enable fast/efficient robotic behavior learning. These challenges include, but not are limited to, human behavior learning/modeling, reinforcement learning under limited human guidance, multi-agent reinforcement learning, human-robot interactive learning.
Position denoscription:
Required
- A Bachelor’s degree in electrical and computer engineering, computer science, mathematics, or a related field;
- Strong background in mathematics, statistics, and machine learning;
- Excellent writing and communication skills;
- Proficiency in C++ or Python.
Preferred
- Master’s degree
- Experience on Robot Operating System (ROS), reinforcement learning, and computer vision
- Experience on Tensorflow, Keras, or PyTorch.
- Demonstrated research experience (i.e., projects or publications)
How to apply:
Send the following documents in a single PDF file
- One-page cover letter describing your interest, goal, and how your background fits well;
- CV or resume
- Trannoscripts
to yongcan.cao@utsa.edu
✔️ @ApplyTime
The Unmanned Systems Lab at University of Texas at San Antonio has 1-2 fully funded PhD openings in the area of human-guided robotic behavior learning. The main research goal is to develop new human-guided reinforcement learning algorithms to enable fast/efficient robotic behavior learning. These challenges include, but not are limited to, human behavior learning/modeling, reinforcement learning under limited human guidance, multi-agent reinforcement learning, human-robot interactive learning.
Position denoscription:
Required
- A Bachelor’s degree in electrical and computer engineering, computer science, mathematics, or a related field;
- Strong background in mathematics, statistics, and machine learning;
- Excellent writing and communication skills;
- Proficiency in C++ or Python.
Preferred
- Master’s degree
- Experience on Robot Operating System (ROS), reinforcement learning, and computer vision
- Experience on Tensorflow, Keras, or PyTorch.
- Demonstrated research experience (i.e., projects or publications)
How to apply:
Send the following documents in a single PDF file
- One-page cover letter describing your interest, goal, and how your background fits well;
- CV or resume
- Trannoscripts
to yongcan.cao@utsa.edu
✔️ @ApplyTime
Researcher in Federated Learning (IHU Strasbourg)
About the group
The research group CAMMA at IHU Strasbourg is looking for a researcher in machine learning. The successful candidate will perform research in federated learning for medical data to develop generalizable and efficient ML (e.g., self-supervision, domain shift, improved data utility detection). The candidate must have a PhD in computer science with background in machine learning and have demonstrated his research abilities with peer-reviewed publications in top conferences and journals (e.g. CVPR, ICLR, MICCAI, etc.). The ideal candidate has proven experience in Federated Learning through publication(s) and/or code (e.g. Github). Background in medical data (e.g., imaging, health records, genomics, etc.) is a plus but not a requirement. The candidate will have the opportunity to work with a multidisciplinary team of researchers and clinicians in France and Europe and shape research. In parallel, they will also have the chance to work together with top industry partners through MLCommons to develop better tools for medical AI and thus gain major visibility. Salary is competitive, and appointment duration is 2 years with the possibility of extension.
About the Project
CLINNOVA is a European initiative of the Greater Region (http://www.granderegion.net/) which groups together French region Grand Est, Belgian Federation Wallonia-Brussels and Ostbelgien, German Saarland and Rhineland-Palatinate as well as the Grand Duchy of Luxembourg. CLINNOVA project aims at unlocking the potential of Artificial Intelligence (AI) and data science in healthcare, with the ambition to establish a European standard model, which is sovereign, open, and interoperable. The overall goal of CLINNOVA is to enable data-driven health environment for AI solutions, which is based both on infrastructure investment and coordination between clinical players. The initiative aims to create a federated infrastructure of large prospective normalized multimodal medical data (e.g., biobanking, imaging) between participating institutes with a focus on autoimmune, inflammatory and cancer diseases. Research and development of AI algorithms on this massive amount of federated data is a unique exciting opportunity from computer science and clinical perspectives.
Skills/Qualifications
Perform research in Federated Learning algorithms
Publish peer-reviewed papers
Participate in research meetings with top industry partners and contribute code to open research community (e.g. MLCommons)
Mentor interns
Machine Learning Background
Python or other language
PyTorch, Keras, or Tensorflow
Please submit your cover letter and CV at alexandros.karargyris [at] ihu-strasbourg.eu
✔️ @ApplyTime
About the group
The research group CAMMA at IHU Strasbourg is looking for a researcher in machine learning. The successful candidate will perform research in federated learning for medical data to develop generalizable and efficient ML (e.g., self-supervision, domain shift, improved data utility detection). The candidate must have a PhD in computer science with background in machine learning and have demonstrated his research abilities with peer-reviewed publications in top conferences and journals (e.g. CVPR, ICLR, MICCAI, etc.). The ideal candidate has proven experience in Federated Learning through publication(s) and/or code (e.g. Github). Background in medical data (e.g., imaging, health records, genomics, etc.) is a plus but not a requirement. The candidate will have the opportunity to work with a multidisciplinary team of researchers and clinicians in France and Europe and shape research. In parallel, they will also have the chance to work together with top industry partners through MLCommons to develop better tools for medical AI and thus gain major visibility. Salary is competitive, and appointment duration is 2 years with the possibility of extension.
About the Project
CLINNOVA is a European initiative of the Greater Region (http://www.granderegion.net/) which groups together French region Grand Est, Belgian Federation Wallonia-Brussels and Ostbelgien, German Saarland and Rhineland-Palatinate as well as the Grand Duchy of Luxembourg. CLINNOVA project aims at unlocking the potential of Artificial Intelligence (AI) and data science in healthcare, with the ambition to establish a European standard model, which is sovereign, open, and interoperable. The overall goal of CLINNOVA is to enable data-driven health environment for AI solutions, which is based both on infrastructure investment and coordination between clinical players. The initiative aims to create a federated infrastructure of large prospective normalized multimodal medical data (e.g., biobanking, imaging) between participating institutes with a focus on autoimmune, inflammatory and cancer diseases. Research and development of AI algorithms on this massive amount of federated data is a unique exciting opportunity from computer science and clinical perspectives.
Skills/Qualifications
Perform research in Federated Learning algorithms
Publish peer-reviewed papers
Participate in research meetings with top industry partners and contribute code to open research community (e.g. MLCommons)
Mentor interns
Machine Learning Background
Python or other language
PyTorch, Keras, or Tensorflow
Please submit your cover letter and CV at alexandros.karargyris [at] ihu-strasbourg.eu
✔️ @ApplyTime
PhD Positions: A Practical Theory of Computation for Modern Neural Network Architectures
The Natural Language Processing Group at Linköping University and the Foundations of Language Processing Group at Umeå University are announcing two (2) fully-funded PhD Positions in Computer Science.
The positions are announced in the project “A Practical Theory of Computation for Modern Neural Network Architectures”, headed by Marco Kuhlmann (Linköping) and Frank Drewes (Umeå). The aim of this project is to develop a practical theory of computation for modern neural network architectures by combining methods from theoretical computer science with empirical validation in natural language processing (NLP).
For more information about the project and the positions, please see the following web page:
https://liu-nlp.github.io/wasp-2021/
The application deadline is 2021-09-30.
Best regards
Marco Kuhlmann
Professor
Department of Computer and Information Science
Linköping University
Sweden
✔️ @ApplyTime
The Natural Language Processing Group at Linköping University and the Foundations of Language Processing Group at Umeå University are announcing two (2) fully-funded PhD Positions in Computer Science.
The positions are announced in the project “A Practical Theory of Computation for Modern Neural Network Architectures”, headed by Marco Kuhlmann (Linköping) and Frank Drewes (Umeå). The aim of this project is to develop a practical theory of computation for modern neural network architectures by combining methods from theoretical computer science with empirical validation in natural language processing (NLP).
For more information about the project and the positions, please see the following web page:
https://liu-nlp.github.io/wasp-2021/
The application deadline is 2021-09-30.
Best regards
Marco Kuhlmann
Professor
Department of Computer and Information Science
Linköping University
Sweden
✔️ @ApplyTime
Ph.D. student / Postdoc position in machine learning with spiking neurons at University of Bremen, Germany
You looked at our paper Back-Propagation Learning in Deep Spike-By-Spike Networks ( https://www.frontiersin.org/articles/10.3389/fncom.2019.00055/full ) and thought "Interesting idea but I can improve that!" then you may want to tell us your idea... You could end up working on it as a Ph.D. student / Postdoc for the next three years in Bremen, Germany.
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The Computational Neuroscience group of Klaus Pawelzik invites applications for an open Ph.D. student / Postdoc position (E13 TV-L 100% for 3 years; all genders welcome) in the project "Efficient Implementation of Spike-by-Spike Neural Networks using Stochastic and Approximative Techniques". We are looking for a person with a strong background in mathematics, programming, and machine learning as well as an intense interest in neuroscience. Someone who is not afraid of cooperating with engineers, since this is a joint project with a focus on hardware development.
The overarching goal of our project is to improve the efficiency of spiking artificial neural networks using hardware and algorithmic approximation techniques. Specifically, the project focuses on Spike-by-Spike networks since they offer a balance between computational requirements and biological-realism which keeps the advantages of the biological networks while enabling a compact technical realization. To fully take advantage of the unique features of SbS in terms of robustness and sparseness, dedicated hardware architectures are required.
You would join in with numerical simulations, theoretical analyses, as well as through the development of new ideas and approaches for boosting the performance and capabilities of the Spike-By-Spike model. Furthermore, you would also work on combining Spike-By-Spike networks with non spiking deep neuronal networks into hybrid models.
The details can be found at http://www.neuro.uni-bremen.de/content/open-position-sbs
✔️ @ApplyTime
You looked at our paper Back-Propagation Learning in Deep Spike-By-Spike Networks ( https://www.frontiersin.org/articles/10.3389/fncom.2019.00055/full ) and thought "Interesting idea but I can improve that!" then you may want to tell us your idea... You could end up working on it as a Ph.D. student / Postdoc for the next three years in Bremen, Germany.
-------------
The Computational Neuroscience group of Klaus Pawelzik invites applications for an open Ph.D. student / Postdoc position (E13 TV-L 100% for 3 years; all genders welcome) in the project "Efficient Implementation of Spike-by-Spike Neural Networks using Stochastic and Approximative Techniques". We are looking for a person with a strong background in mathematics, programming, and machine learning as well as an intense interest in neuroscience. Someone who is not afraid of cooperating with engineers, since this is a joint project with a focus on hardware development.
The overarching goal of our project is to improve the efficiency of spiking artificial neural networks using hardware and algorithmic approximation techniques. Specifically, the project focuses on Spike-by-Spike networks since they offer a balance between computational requirements and biological-realism which keeps the advantages of the biological networks while enabling a compact technical realization. To fully take advantage of the unique features of SbS in terms of robustness and sparseness, dedicated hardware architectures are required.
You would join in with numerical simulations, theoretical analyses, as well as through the development of new ideas and approaches for boosting the performance and capabilities of the Spike-By-Spike model. Furthermore, you would also work on combining Spike-By-Spike networks with non spiking deep neuronal networks into hybrid models.
The details can be found at http://www.neuro.uni-bremen.de/content/open-position-sbs
✔️ @ApplyTime
Frontiers
Back-Propagation Learning in Deep Spike-By-Spike Networks
Artificial neural networks (ANNs) are important building blocks in technical applications. They rely on noiseless continuous signals in stark contrast to the discrete action potentials stochastically exchanged among the neurons in real brains. We propose…
PhD scholarship in NLP
PhD scholarships are available in the area of machine learning with application to sentiment analysis, social networks and facial expressions.
Preference will be given to candidates with a masters, at least one research publication and 6 months full time work experience.
Application deadline is end of 30th Sep 2021.
https://www.jcu.edu.au/graduate-research-school/how-to-apply
For further discussion kindly email your resume to i.chaturvedi@uq.edu.au
✔️ @ApplyTime
PhD scholarships are available in the area of machine learning with application to sentiment analysis, social networks and facial expressions.
Preference will be given to candidates with a masters, at least one research publication and 6 months full time work experience.
Application deadline is end of 30th Sep 2021.
https://www.jcu.edu.au/graduate-research-school/how-to-apply
For further discussion kindly email your resume to i.chaturvedi@uq.edu.au
✔️ @ApplyTime
Dear All,
We have a postdoc position at City University of Hong Kong. The research will be on reinforcement learning in medical/robotics applications. To apply, please send your CV to enek...@cityu.edu.hk
Contact information:
Ehsan Nekouei
Email: enek...@cityu.edu.hk
Web: http://www.ee.cityu.edu.hk/~enekouei/index.html
Best,
Ehsan
✔️ @ApplyTime
We have a postdoc position at City University of Hong Kong. The research will be on reinforcement learning in medical/robotics applications. To apply, please send your CV to enek...@cityu.edu.hk
Contact information:
Ehsan Nekouei
Email: enek...@cityu.edu.hk
Web: http://www.ee.cityu.edu.hk/~enekouei/index.html
Best,
Ehsan
✔️ @ApplyTime
Systems neuroscience research assistant position in Florida. Sleep and memory
One Research Assistant or Master’s Student position in the laboratory of Dr. Carmen Varela (Psychology Department, Florida Atlantic University; https://www.varelalab.org/) to investigate biomarkers of sleep cellular activity in the thalamus that correlate with sleep depth and stability. Keywords: behaving rodent extracellular electrophysiology, cell spike dynamics, learning and memory, sleep fragmentation.
Start date January 2022 (some flexibility).
*** Requirements ***
Interested candidates please send your curriculum and a brief denoscription of your research interests to varelac@fau.edu We are looking for team-oriented candidates, ideally with prior experience in rodent behavior and electrophysiology. Candidates selected for an interview will be asked to provide contact information for up to three references.
*** What you get ***
· Work on exciting and impactful projects to understand the contribution of thalamic cells to sleep and memory.
· Develop research skills using state-of-the-art systems and pharmacology techniques in rodents.
· Mentorship, supportive lab environment, in a rapidly growing neuroscience campus.
Location: The Varela laboratory is located in FAU’s Jupiter campus, a rapidly growing neuroscience hub, which also hosts our partners the Max Planck Florida Institute for Neuroscience and Scripps Research Institute.
FAU is an equal opportunity/affirmative action institution and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veterans’ status or any other characteristic protected by law.
✔️ @ApplyTime
One Research Assistant or Master’s Student position in the laboratory of Dr. Carmen Varela (Psychology Department, Florida Atlantic University; https://www.varelalab.org/) to investigate biomarkers of sleep cellular activity in the thalamus that correlate with sleep depth and stability. Keywords: behaving rodent extracellular electrophysiology, cell spike dynamics, learning and memory, sleep fragmentation.
Start date January 2022 (some flexibility).
*** Requirements ***
Interested candidates please send your curriculum and a brief denoscription of your research interests to varelac@fau.edu We are looking for team-oriented candidates, ideally with prior experience in rodent behavior and electrophysiology. Candidates selected for an interview will be asked to provide contact information for up to three references.
*** What you get ***
· Work on exciting and impactful projects to understand the contribution of thalamic cells to sleep and memory.
· Develop research skills using state-of-the-art systems and pharmacology techniques in rodents.
· Mentorship, supportive lab environment, in a rapidly growing neuroscience campus.
Location: The Varela laboratory is located in FAU’s Jupiter campus, a rapidly growing neuroscience hub, which also hosts our partners the Max Planck Florida Institute for Neuroscience and Scripps Research Institute.
FAU is an equal opportunity/affirmative action institution and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veterans’ status or any other characteristic protected by law.
✔️ @ApplyTime