瑞士苏黎世联邦理工学院2025年博士后招聘（强化学习）

ETH Zurich

Postdoctoral Researcher in Reinforcement Learning

The ODI group at the Institute of Machine Learning is looking for highly motivated postdoctoral researchers with expertise in reinforcement learning (RL) to join our team.

The position is available immediately, with an initial appointment for 1 year, renewable up to 3 years based on performance.

Job description

The candidate is expected to work on the broad theme of reinforcement learning (RL), such as (but not limited to)

Theory of online learning, reinforcement learning, and data-driven control

Learning in games, and multi-agent RL

RLHF and alignment in LLMs

Representation learning in RL

Transfer learning in multi-task bandits and RL

Statistical or generative decision making

The exact project scope will be tailored to the candidate's strength and expertise. The candidate is expected to collaborate closely with the research supervisor and the ODI team members, and assist in mentoring Master’s or Bachelor’s thesis projects.

Profile

We are seeking candidates with:

A PhD degree in the field of Computer Science or similar

Solid background in the foundations of reinforcement learning

Proven research experience with first-authored publications at peer-reviewed conferences (ICML, ICLR, NeurIPS, CoRL, ICRA, AAAI, AAMAS or similar)

A collaborative mindset, with the ability to work effectively within a multidisciplinary team

(Optional) Experience with large-scale machine learning codebases

We offer

Environment and resources: We promise an inspiring, collaborative research environment to support your immersion into an ambitious research agenda. Our team consists of a dynamic and international group of researchers who share a common vision to contribute to top-level academic research in the fields of machine learning.(For more postdoctoral recruitment information, visit:boshihoujob.com) You will have access to state-of-the-art computational resources and a broad network of global collaborators.

Compensation: We offer a competitive salary. For employment details at ETH Zurich, visit ETH Zurich Employment Information.

Working, teaching and research at ETH Zurich

We value diversity and sustainability

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future.

Curious? So are we.

We look forward to receiving your complete online application with the following documents:

Curriculum Vitae

Complete publication list

Brief research statement (2 pages) describing your expertise and interests

Contact information of 2-3 references

Copies of academic certificates

Note: Applications must be submitted through our online portal. We will not accept applications sent via email.

For any questions regarding the position, please contact Dr. Zebang Shen at zebang.shen@inf.ethz.ch.

About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Job details

Title

Postdoctoral Researcher in Reinforcement Learning

Employer

ETH Zürich

Location

Rämistrasse 101 Zurich, Switzerland

Published

2025-10-07

Application deadline

Unspecified

Job type

Postdoc

Field

Systems Engineering, Artificial Intelligence, Distributed Computing, Programming Languages, Machine Learning

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