The Division of Data Science and AI, Department of Computer Science and Engineering at Chalmers is looking for a postdoc interested in developing machine learning algorithms.
About us
You will join the Healthy AI Lab, a research group led by Associate Professor Fredrik Johansson, that develops machine learning methods and theory to improve data-driven decision-making in healthcare.
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.
About the research project
In this project, you will become part of a team of researchers working on fundamental aspects of data-driven decision-making inspired by, and applied to, problems in healthcare. Currently, we are investigating transferable and interpretable models for tabular data, efficient learning paradigms for medical imaging, and causally grounded and identifiable representation learning. You will have great freedom to influence your research agenda within these and related themes. Our group emphasizes methods strongly supported by theory.
What you will do
- You will do research within the themes of the research group, aimed at the highest international standard
- You will assist in the supervision of PhD students, and possibly MSc students, advised by the lab PI
- You are expected to attend conferences and events related to the project and engage regularly with the Healthy AI lab through group meetings and seminars
- Additionally, you will dedicate 20% of your time to teaching, which may include lecturing, TAing, or supervising students.
The position is meritorious for future roles in academia, industry, or the public sector.
