PhD Student Position in Machine Learning Theory and Data Efficiency

Publiceringsdatum: 2025-06-13

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Jobbannons

We are offering a PhD student position in machine learning (ML) theory, focusing on new methods for training models with a limited amount of data. The student will be a part of a new NEST initiative, Time-Resolved Imaging and Multi-Channel Evaluation of Cellular Dynamics (TIMED). This project is a 5-year collaboration between researchers at Chalmers University of Technology, Uppsala University, and Karolinska Institute.

About us 

The Department of Computer Science and Engineering (CSE) is a joint department between Chalmers and the University of Gothenburg and is internationally recognized for its excellence in research and education. We host around 300 employees from over 40 countries in a stimulating, collaborative environment. Gothenburg, Sweden's second-largest city, consistently ranks as one of the world’s most sustainable and livable cities.

The PhD student will join Panahi’s research group at the Data Science and AI division, CSE department, Chalmers. The goal of this group is to bring together the theory of optimization algorithms and high-dimensional statistics to address some of the most fundamental questions in ML such as the behavior of neural networks. The environment of this project is highly collaborative, bringing together researchers from diverse backgrounds who share a commitment to rigorous, open, and impactful science. The project is part of the DDLS and WASP initiatives, which aim to position Sweden at the forefront of computational life sciences and AI research.

The PhD student will belong to the graduate school within the Wallenberg AI, Autonomous Systems and Software Program (WASP). WASP is Sweden's largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish society and industry. Read more: https://wasp-sweden.org/

About the research project  

The project is a unique opportunity to work on fundamental theoretical questions in ML, and at the same time make an impact in a real-world application.

Our goal is to describe the performance of ML methods when limited data is available. Large neural networks are known to be heavily inefficient in this limit, and we aim to discover better methods for this purpose. We would like to study how prior domain knowledge and trained models on similar problems can be both incorporated to train better models and guide researchers to design better experiments. 

The project will be in collaboration with other NEST partners, who collect and process biological behavior of live cells by imaging. The methods developed in this project will be used to improve the best practices in this application 

Who we are looking for: 

• To qualify as a PhD student, you must have a Master's degree in a relevant field to theory of machine learning and AI. This includes, but is not limited to, computer science, electrical engineering, physics and mathematics.  
• You will need strong written and verbal communication skills in English. 
• Some level of familiarity with computer programming is rquired. 

Additional Merrits (documents should be attached):

• Previous projects or course work related to machine learning implementations
• Previous projects or course work involving mathematical proving
• Solid knowledge of Python 

What you will do: 

• Develop your own scientific concepts and communicate the results of your research verbally and in writing 
• Collaborate with other researchers within the TIMED NEST project to build better models and experiments for live cell images.
• As a member of the DSAI division, PhD students will be involved in teaching activities offered by the division
• Take courses at an advanced level within the Graduate school of Computer Science and Engineering. 

Contract terms and what we offer: 

• The PhD positions are fully funded from start. 
• As a PhD student at Chalmers, you are an employee and enjoy all employee benefits. Read more about working at Chalmers and our benefits for employees. 
• The position is limited to four years, with the possibility to teach up to 20%, which extends the position to five years. 
• 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. 
• A dynamic and inspiring working environment in the coastal city of Gothenburg. 
• A starting salary of 34,550 SEK per month (valid from May 25, 2025).
• Read more about Sweden’s generous parental leave, subsidized day care, free schools, healthcare etc at Move To Gothenburg. 

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

Discover more 

Find more general information about doctoral studies at Chalmers here.  

Application procedure 

To apply, please click this link to go to Chalmer's vacancy page. 

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 July 21st, 2025

For questions, please contact:  

Ashkan Panahi 

Associate Professor

Email: ashkan.panahi@chalmers.se

Phone Number: +46732513792

Co-supervising team: Professor Ola Spjuth (ola.spjuth@uu.se), Group Leader Brinton Seashore-Ludlow (b.seashoreludlow@scilifelab.se), Assistant Professor Prashant Singh (prashant.singh@it.uu.se), Assistant Professor Rocío Mercado Oropeza (rocio.mercado@chalmers.se)

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. *