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Doctoral student in hierarchical reinforcement learning for "AI for Math".
Chalmers University of Technology

Doctoral student in hierarchical reinforcement learning for "AI for Math".

2026-06-18 (Europe/Stockholm)
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About the employer

Our goal is to focus on competence, knowledge and collaboration in order to play an important, demonstrable role in social development.

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Are you interested in AI, in particular, reinforcement learing? We are looking for an enthusiastic and motivated student to join us as a Ph.D., student in the Data Science and AI (DSAI) division at Chalmers to explore exciting new directions with hierarchical reinforcement learning!

About us 

The Department of Computer Science and Engineering, a joint department of Chalmers and the University of Gothenburg, spans the breadth of computing disciplines. Our internationally visible research, strong industry links and diverse environment create a collaborative setting where ideas grow into real impact.

At the division of Data Science and AI, we develop data-driven methods and AI solutions that support intelligent decisions across society, advancing machine learning techniques, from foundations to industrial and scientific applications.

There has been a long standing and world leading research programme in formalizing mathematics at the department, funder by ERC advanced grants and Wallenberg projects. A new initiative is to bring in AI techniques into automating theorem provers and proof assistants for the exciting new area of "AI for math". A new research group has crystallized that brings together expertise from several areas besides AI, including formal methods, theorem proving, NLP and cognitive science. The group has a network of very strong international collaborators that the student will become a part of  - we will be organizing a seminar on the theme at a Mittag -Leffler conference on "Ai for Math".

About the research project  

The project is about build on recent advances in heierarchical reinforcement learning (HRL) and to explore its use in AI for Math. Can HRL techniques be used to automate proofs and generate interesting conjectures and lemmas in an interactive theorem prover? Human mathematicians typically decompose a big proof into smaller lemmas. HRL is a natural technique to create an automated system to decompose proofs into smaller components. For exciting developments in the area of "AI for Math", see the blog posts of Terry Tao, one of the world's top mathematicians.

The project is funded by WASP, Sweden's national AI initiative and will be carried out in a strong research environment in this area, in collaboration with ERC advanced grant projects (of faculty in the division).  

Who we are looking for

The following requirements are mandatory:

  • To qualify as a Doctoral student, you must have a Master's degree in Computer Science, Mathematics or related fields.  For students with an education earned outside of Sweden, a 4-year Bachelor’s degree is acceptable.
  • Strong written and verbal communication skills in English 
  • You should have strong background in theoretical computer science, foundational AI/machine learning or mathematics and have strong coding skills  in python (or C, C++, Java etc).
  • You should have a strong background in modern machine learning - you should have taken good courses in basic ML and in particular have the rudiments of reinforcement learning.

The following experience will strengthen your application: 

  • Experience with logic, a theorem prover or interactive proof assistant is a bonus

What you will do

  • Conduct research and aim for publications in top venues in modern AI (such as NeurIPS, ICML, AAAI etc).Take courses at an advanced level within the WASP Graduate school.
  • Develop your own scientific concepts and communicate the results of your research verbally and in writing 
  • The position generally also includes teaching on Chalmers' undergraduate level or performing other duties corresponding to 20 percent of working hours

Contract terms  

  • The Doctoral student positions are fully funded from start. 
  • The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which extends the position up to five years. 
  • A starting salary of 35,725 SEK per month (valid from May 1, 2026). 
  • Doctoral studies require physical presence throughout the entire study period. A valid residence permit must be presented by the study start date; otherwise the admission may be withdrawn. 

What we offer 

  • As a Doctoral student at Chalmers, you are an employee and enjoy all employee benefits. Read more about  working at Chalmers  and our benefits for employees. 
  • A dynamic and inspiring working environment in the coastal city of Gothenburg
  • Read more about Sweden’s generous parental leave, subsidized day care, free schools, healthcare etc at Move To Gothenburg. 

Chalmers is dedicated to improving gender balance and actively works with equality projects, such as the GENIE Initiative for gender equality and excellence. We celebrate diversity and consider equality and inclusion as fundamental aspects of all our activities. 

If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in.

Find more general information about doctoral studies at Chalmers here.  

Application procedure 

The application should be written in English and attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files. 

CV 

Personal letter 

  • A brief introduction about yourself. 
  • A brief motivation as to why you are interested in this position. 

Bachelor’s and, if available, master’s thesis together with the transcripts. 

Use the button at the foot of the page to reach the application form.  

Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered. Contact details to references will be requested after the interview. 

We welcome your application no later than June 18, 2026.

For questions, please contact:  

Devdatt Dubhashi
Professor
[email protected]

We look forward to your application! 

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***  

 Chalmers University of Technology in Gothenburg conducts research and education in technology and natural sciences at a high international level. The university has 3100 employees and 10,000 students, and offers education in engineering, science, shipping and architecture. With scientific excellence as a basis, Chalmers promotes knowledge and technical solutions for a sustainable world. Through global commitment and entrepreneurship, we foster an innovative spirit, in close collaboration with wider society. 
Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. 

Chalmers University of Technology conducts research and education in engineering sciences, architecture, mathematical sciences, natural and nautical sciences, working in close collaboration with industry and society. The strategy for scientific excellence focuses on our eight Areas of Advance; Built Environment, Energy, Information & Communication Technology, Life Science, Materials Science, Nanoscience & Nanotechnology, Production and Transport. The aim is to make an active contribution to a sustainable future using the basic sciences as a foundation and innovation and entrepreneurship as the central driving forces. Chalmers has around 11,000 students and 3,000 employees. New knowledge and improved technology have characterised Chalmers since its foundation in 1829, completely in accordance with the will of William Chalmers and his motto: Avancez!

Job details

Title
Doctoral student in hierarchical reinforcement learning for "AI for Math".
Location
Maskingränd 2 Gothenburg, Sweden
Published
2026-05-18
Application deadline
2026-06-18 23:59 (Europe/Stockholm)
2026-06-18 23:59 (CET)
Job type
PhD
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About the employer

Our goal is to focus on competence, knowledge and collaboration in order to play an important, demonstrable role in social development.

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