PhD Candidate in Complex Reinforcement Learning and Geometrical Aperiodic Environments at the Donders Centre for Cognition

27 May 2023
Job Information

Organisation/Company

Radboud University

Research Field

Cultural studies

Researcher Profile

Recognised Researcher (R2)
First Stage Researcher (R1)

Country

Netherlands

Application Deadline

23 Jun 2023 - 22:00 (UTC)

Type of Contract

Temporary

Job Status

Not Applicable

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Do you have a strong background in scientific programming and experience with open-source code practices? And do you want to collaborate and interact with renowned international experts in machine learning, computational neuroscience and neuromorphic computing? Then join us at the Donders Institute. As a PhD Candidate, you will be responsible for innovating and creating state-of-the-art algorithms in complex systems.

We invite applications for a PhD position on reinforcement learning for aperiodic structures, with emphasis on single and multi-agent learning. This project is embedded in the Donders institute and the AI department of Radboud University. The aim is to develop robust reinforcement learning algorithms and gym environments to tackle navigation in aperiodic structures, with emphasis on task achievement and agent communication. This work entails a theoretical (mathematical) understanding of random systems, dynamic information theory and deep reinforcement learning, alongside testing and/or implementation of these algorithms in the form of novel gym environments for agent-based artificial neural network modelling. As a PhD candidate, you will be responsible for development and validation of the math and models under supervision of expert staff in machine learning.

We offer you a full time (100%) position for 4 years. This project is supervised by Dr Tal Kachman and Prof. van Gerven (PhD supervisor). You will be employed at the Artificial Intelligence department of the Donders Institute for Brain, Cognition and Behaviour and have the opportunity to collaborate and interact with renowned international experts in machine learning, computational neuroscience and neuromorphic computing. You will also benefit from the extensive training programme offered by the Donders Graduate School. Additionally, you will have the opportunity to supervise MSc and BSc students in their (honours) thesis projects.

You will be responsible for innovating and creating state-of-the-art algorithms in complex systems such as reinforcement learning environments with emphasis on multi-agent interactions. This will also entail creating production level research code in Python, C++, and generating open-source knowledge base. Knowledge dissemination is an integral part, and you will be expected to publish extensively as well as give invited seminars talks and produce general-purpose
content such as blogs.

This position does not include a teaching assignment.

Requirements
Specific Requirements

• You should have exceptional mathematical skills and a deep understanding of reinforcement learning with emphasis on complex interactions, dynamical systems, deep learning, machine learning and algorithmic foundations.
• You will be expected to have a strong background in scientific programming, experience with open-source code practices with a proven code base, and a track record of publications in the aforementioned fields.
• You should also have experience with mentoring and guiding students and collaborative work.
• Ideally, you will also have a proven track record of performing research in international environments.

Additional Information
Benefits

• It concerns an employment for 1.0 FTE.
• The gross starting salary amounts to €2,541 per month based on a 38-hour working week, and will increase to €3,247 in the fourth year (salary scale P ).
• You will receive 8% holiday allowance and 8.3% end-of-year bonus.
• You will be employed for an initial period of 18 months, after which your performance will be evaluated. If the evaluation is positive, the contract will be extended by 2.5 years (4 year contract).
• You will be able to use our Dual Career and Family Care Services . Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen.
• Working for us means getting extra days off. In case of full-time employment, you can choose between 30 or 41 days of annual leave instead of the legally allotted 20.
• You will be part of the Donders Graduate School for Cognitive Neuroscience

Work and science require good employment practices. This is reflected in Radboud University's primary and secondary employment conditions . You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself, for example, exchange income for extra leave days and receive a reimbursement for your sports subscription. And of course, we offer a good pension plan. You are given plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes.

Selection process

You can apply until 23 June 2023, exclusively using the button below. Kindly address your application to Tal Kachman. Please fill in the application form and attach the following documents:

• A motivation letter
• Your CV, including two recommendation letters
• A peer-reviewed preprint
• An open-source code reference

The first round of interviews will take place on Wednesday 19 July. The second round of interviews will take place on Monday 24 July. You would preferably begin employment as soon as possible.
We can imagine you're curious about our application procedure . It offers a rough outline of what you can expect during the application process, how we handle your personal data and how we deal with internal and external candidates.

Additional comments

For questions about the position, please contact Tal Kachman, Assistant Professor at [email protected] .

Website for additional job details

https://www.academictransfer.com/328411/

Work Location(s)

Number of offers available

1

Company/Institute

Radboud University

Country

Netherlands

City

Nijmegen

Postal Code

6525 XZ

Street

Houtlaan 4

Where to apply

Website

https://www.academictransfer.com/328411/phd-candidate-in-complex-reinforcement-…

Contact

City

Nijmegen

Website

http://www.ru.nl/

Street

Houtlaan 4

Postal Code

6525 XZ

STATUS: EXPIRED