PhD Student in Computational Structural Biology of Pathogen Targets

Start date is by mutual arrangement, with the possibility to start immediately

How does life emerge from molecules and cells? This is the central question that motivates us. With curiosity and passion, we investigate the entire spectrum ranging from the atom to the organism. The Biozentrum of the University of Basel is one of the world’s leading life sciences institutes. With 32 groups and 500 employees, we are a dynamic and international research community that has spawned many fundamental discoveries in biology and medicine as well as several Nobel Laureates. Become part of our community!

In Prof. Torsten Schwede's group we use computational methods, with a strong focus on artificial intelligence, for integrative modelling of macromolecular complexes, including protein assemblies, protein-ligand interactions, and conformational changes. Our research also aims to understand and predict protein-protein complementarity, design artificial protein binders, investigate the effects of mutations on protein structure and function, and apply protein representation learning to uncover hidden links in the dark proteome.

At the SIB Swiss Institute of Bioinformatics, we develop SWISS-MODEL (https://swissmodel.expasy.org), a widely used web-based platform for generating high-accuracy 3D models of protein structures and complexes for application in life sciences. In addition, we develop and maintain PLINDER, a resource designed to drive breakthroughs in deep learning-based protein-ligand complex prediction, as well as the Protein Universe Atlas, an interactive web resource for exploring the vast landscape of publicly available protein sequence and structure data. We also organise community efforts to advance the state of the art in structure prediction through initiatives such as CASP and CAMEO.

Your position

We are looking for a motivated PhD student to apply bioinformatic and molecular modelling methods to study structure–function relationships in pathogen targets. Conducted in collaboration with the NCCR AntiResist initiative, the research will focus on interpreting resistance variants and on structure-based discovery of new antimicrobials. Where appropriate, generated hypotheses will guide experimental validation, with outcomes feeding back into workflow refinement, improving model quality, and supporting the interpretation of underlying biological mechanisms.

Your profile

  • Master degree in chemistry, molecular biology, bioinformatics, biochemistry or a related discipline.
  • Strong interest or experience in deep learning methods for drug discovery, structural biology, biochemistry and modern data analytics techniques.
  • You can strengthen our team in at least one of the following areas: protein bioinformatics, quantum chemistry, data science.
  • Good communication skills in English.
  • Self-motivation, drive and ability to explore new research directions.

We offer

The successful applicant will conduct cutting-edge research using state-of-the-art infrastructure in the Biozentrum, which offers a highly diverse, interdisciplinary, collaborative and stimulating research environment. Salary and benefits are according to University of Basel standards.

Basel is a cosmopolitan and multicultural city at the heart of Europe. Bordering three countries, Switzerland, Germany, and France, Basel provides a high standard of living with a thriving cultural atmosphere. The Basel area is Europe’s most important Life Science hub with many small and medium-size biotech companies as well as global pharmaceutical players.

Application / Contact

The application should include a brief personal statement, explaining how your qualifications and experience relate to the role, together with a full, up-to-date CV, diplomas and two reference letters. Please clearly indicate your preferred starting date.

Review of applications will start immediately and proceed until the position is filled. Only online applications will be considered.

For any informal inquiries, please contact: leila.alexander@unibas.ch

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