Publisher
source

University of Basel

Just Landed

Postdoctoral Position in Reinforcement Learning and Post-Training of Diffusion Language Models University of Basel in Switzerland

Degree Level

Postdoc

Field of study

Computer Science

Funding

The position is funded by a Swiss National Science Foundation project and offers an excellent salary, benefits, and working conditions. It also provides opportunities for conference travel and collaboration with national and international research teams.

Deadline

Nov 20, 2026

Country flag

Country

Switzerland

University

University of Basel

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Keywords

Computer Science
Mathematics
Artificial Intelligence
Reinforcement Learning
Problem Solving
Generative Modeling
Reasoning
Large Language Models
ML

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About this position

The Rhine AI research group, led by Prof. I. Bogunovic in the Department of Mathematics and Computer Science at the University of Basel, Switzerland, invites applications for a postdoctoral position in machine learning and artificial intelligence.

The project, funded by the Swiss National Science Foundation, focuses on the post-training of diffusion-based large language models (dLLMs) and improving their reasoning capabilities. The postdoctoral researcher will develop reinforcement-learning methods, investigate reasoning-aware generation strategies such as adaptive unmasking and credit assignment, and help create benchmarks for evaluating reasoning across domains, including mathematical problem solving.

The successful candidate will lead research directions, mentor PhD students, publish in venues such as ICML, NeurIPS, and ICLR, and collaborate with national and international AI experts, including partners at EPFL and ETH. The position is based in Basel and is available from January 2027 or later.

Applicants should hold a PhD in machine learning or a related field, demonstrate strong publications and mathematical foundations, and have excellent coding and large-scale experimentation skills. Experience with LLMs, reinforcement learning, or generative modeling is desirable. Fluency in spoken and written English is required.

Applications should include a short motivation statement of up to 150 words, a CV with publication list, contact details for recommenders, and a PhD thesis or up to two representative publications. Apply online; applications are encouraged by November 20, 2026, although the search remains open until a suitable candidate is appointed.

Funding details

The position is funded by a Swiss National Science Foundation project and offers an excellent salary, benefits, and working conditions. It also provides opportunities for conference travel and collaboration with national and international research teams.

What's required

Applicants must hold a PhD in machine learning or a related field, have a strong publication record at leading machine learning venues, an exceptional academic record, and a solid mathematical foundation. Strong coding and implementation skills, including the ability to run large-scale experiments, are expected. Experience with large language models, reinforcement learning, or generative modeling is advantageous. Excellent spoken and written English communication skills are required.

How to apply

Prepare the requested application materials as PDF files: a motivation statement of up to 150 words, a CV with publication list, recommender contact information, and a PhD thesis or up to two representative publications. Submit them through the online application portal; applications are encouraged before November 20, 2026, but the position remains open until filled.

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