are looking for candidates with a strong research interest in reinforcement learning,
and particularly the following fields:
1. Exploration in reinforcement learning.
2. Decision making under partial information.
3. Representations of uncertainty in decision making.
4. Theory of reinforcement learning (e.g. PAC/regret bounds)
5. Human-AI collaboration.
The main supervisor will be Christos Dimitrakakis < https://sites.google.com/site/christosdimitrakakis
Examples of our group's past and current research can be found on
include work on Bayesian reinforcement learning, approximate planning, bandit problems,
human-AI collaboration, inverse reinforcement learning, privacy and fairness.
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/
Excellent technical skills in calculus, linear algebra, probability as well as competence in at least one programming language is expected. In addition, the doctoral student must have a strong background, as evidenced by their master thesis, in one of the following areas:
1. Reinforcement learning.
2. Bayesian inference.
3. Game theory.
>>>> Application Information <<<<<
*Starting date* 1 September 2022 or soon afterwards.
*Application deadline* 31 May 2022.
The PhD is fully funded, and normally lasts 4 years, with one course per semester as a teaching assistant.
To apply send an email to christos.d...@unine.ch
with the subject 'PhD Neuchatel'.
An application must include:
1. A statement of research interests and motivation relevant to the position.
2. A CV with a list of references.
3. Your MSc thesis (or a draft) or another research work demonstrating your academic writing.
4. A degree transcript.