We are always interested in hearing from talented and motivated candidates who want to work on computational protein science at the interface of AI, structural biology, and evolution. Our group develops methods for protein structure prediction, protein-protein interactions, proteoform analysis, membrane proteins, and large-scale studies of protein evolution.
What you can work on
Possible project areas include:
- deep learning for protein-protein interactions and complex assembly
- proteoforms, long-read transcriptomics, and proteomics integration
- structure-guided studies of protein evolution and domain architecture
- membrane proteins, topology, and transmembrane protein organization
- flexible protein design, docking, and large-scale structural bioinformatics
Environment
The lab is based at the Department of Biochemistry and Biophysics, Stockholm University, with strong links to SciLifeLab, the Stockholm Bioinformatics Center, the Center for Biomembrane Research, and the Swedish E-science Research Center. We use large-scale computational resources, including Berzelius, and collaborate broadly across computational and experimental groups.
Who we are looking for
We welcome applicants with backgrounds in:
- bioinformatics
- computer science
- machine learning
- structural biology
- physics
- mathematics
- statistics
- computational chemistry
- related quantitative disciplines
We particularly value candidates who enjoy working across disciplinary boundaries and are excited by both method development and biological discovery.
Why this is a good place to train
The group has a long track record in computational structural biology and bioinformatics, substantial competitive funding, and a strong record of trainee development. Former students and postdocs from the lab have gone on to faculty and tenure-track positions at institutions in Sweden and internationally.
Current directions
Current projects in the lab include:
- proteome-scale prediction of protein interactions and complexes
- modelling proteoforms from transcriptomic and proteomic data
- structural analysis of domain rearrangements across the tree of life
- flexible protein design and docking
- RNA structure prediction and deep learning for molecular systems
How to apply
For prospective PhD students and postdocs, please email:
- a short statement of interest
- your CV
- links to publications, code, or thesis work
- names of referees or references
If no formal opening is currently advertised, strong unsolicited applications are still welcome.
Contact
For informal enquiries, please use the contact details on the Contact page.