Connectionists: PhD Position in Reinforcement Learning, Fairness or Privacy

[Christos Dimitrakakis]

PhD Scholarship in reinforcement learning, privacy, or fairness at the 
university of Neuchatel, Swizerland

We are looking for a PhD student to join our group on reinforcement
learning and decision making under uncertainty more generally, 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 is required. Within the area, we are looking for candidates
with a strong research interest in the following fields

- Reinforcement learning and decision making under uncertainty:
1. Exploration in reinforcement learning.
2. Decision making nuder partial information.
3. Representations of uncertainty in decision making.
4. Theory of reinforcement learning (e.g. PAC/regret bounds)
5. Bayesian inference and approximate Bayesian methods.

- Social aspect of machine learning
1. Theory of differntial privacy.
2. Algorithms for differentially private machine learning.
3. Algorithms for fairness in machine learning.
4. Interactions between machine learning and game theory.
5. Inference of human models of fairness or privacy.

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 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/ ).



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. Fairness.
2. Privacy.
3. Reinforcement learning.
4. Game theory.
5. Economics.
6. Statistical inference.

 >>>> 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 approximate 
25% of the time as a teaching assistant.

To apply sen an email to christos.dimitrakakis at 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.