Postdoctoral Fellow Position at Carnegie Mellon University
Deep Reinforcement Learning techniques for multi-agent systems
OPEN POSITION: A postdoctoral fellow position at Carnegie Mellon University
SUPERVISOR:
Prof. Katia Sycara (katia@cs.cmu.edu)
The Robotics Institute, Carnegie Mellon University
Website: http://ri.cmu.edu/ri-faculty/katia-sycara
LOCATION:
The Advanced Agent-Robotics Technology Lab
The Robotics Institute, Carnegie Mellon University
Pittsburgh, Pennsylvania, USA
DESCRIPTION:
The successful candidate will work on Deep Reinforcement Learning algorithms for single and preferably multi-agent planning and learning where some of the agents could be humans.
The position is available immediately, however the start date is negotiable, depending on candidate circumstances. The expected duration of the position is two years with possible additional renewal upon review.
QUALIFICATIONS:
- PhD in a field related to robotics and/or AI.
- A strong theoretical background in Machine Learning, multi-agent planning, decision-making under uncertainty, swarm robotics, and/or human-robot interaction
- Programming skills including experiences using C++, Python, and/or MATLAB, Neural Network programming tools, eg pytorch
- Ability to present work clearly both written and orally
- Experiences with ROS and deep learning.
APPLICATION DETAILS:
Applicants should provide the following material via email to Prof. Katia Sycara (katia@cs.cmu.edu). Please use the subject line: “Postdoc application”. Applications will be reviewed as they are received.
- A curriculum vitae
- A statement of research expertise and interests (up to 2 pages)
- Up to 3 publications
- Names and contact information of three references
- Dates of availability
- A personal website, if available, where further details can be found
DUTIES AND RESPONSIBILITIES
The postdoc will (a) carry out high quality research and publish the research results in the area of learning for multiple agents and human-agent teams, (b) assist in research supervision and guidance of graduate and undergraduate students, © present research results to sponsors, (d) participate in research proposal preparation.