The Department of Physics, Chemistry and Biology, Linköping University, conducts research and offers education at undergraduate and postgraduate levels. Research, the predominant activity, is often done in collaboration with corporate and international partners. We are one of the university’s largest, oldest and most well known departments, encompassing five interacting scientific fields: biology, chemistry, material physics, applied physics and theory and modelling.
We are now looking to appoint a Postdoc in artificial intelligence for structural bioinformatics and cryo-EM formally based at the Department of Physics, Chemistry, and Biology (IFM).
Work assignments
This position is part of a joint collaboration between the two largest research programs in Sweden, the Wallenberg AI, Autonomous Systems and Software Program (WASP) and the SciLifeLab and Wallenberg National Program for Data-Driven Life Science (DDLS), with the ultimate goal of solving ground-breaking research questions across disciplines.
This position is part of the post-doctoral research project “Data-driven application to protein-protein interactions”, which is a joint interdisciplinary research project between professor Björn Wallner at Linköping University (Björn Wallner – LiU) and associate professor Alexey Amunts at SciLifeLab (Alexey Amunts – SU) with aim of using and develop AI methods to understand protein-protein interactions and apply them to biologically relevant problems for which we have cryo-EM data. The project involves using existing methods, i.e., AlphaFold, and developing new AI methods that are specific tailored to the problem and the data available. The position is based at the AI structural biology group at LiU, but it also includes extensive collaborations with the cryo-EM group at SciLifeLab.
We are looking for a motivated, independent postdoc researcher in AI and machine learning and/or structural biology eager to learn new methodologies. Central to the project is the development of methods that incorporate experimental data or prior information into the AI methods to improve predictions and modeling capabilities.