Postdoctoral position in structure-based drug design using machine learning

Uppsala universitet

12d • Onsite

About The Position

Uppsala University’s Department of Cell and Molecular Biology is seeking a postdoctoral researcher for Prof. Jens Carlsson’s research group, part of the Computational Biology and Bioinformatics program. The international group develops and applies molecular modeling techniques to study protein–ligand interactions, with a focus on GPCRs and designing ligands for these therapeutically important targets. The group is also affiliated with Science for Life Laboratory.

The project will develop and apply structure-based virtual screening techniques to identify ligands for peptide-binding GPCRs in large chemical libraries. It will use molecular docking and machine learning to screen combinatorial libraries of peptides and peptidomimetics, as well as collections of naturally occurring peptides from microbes, plants, and animals. The work includes collaborations with experimental research groups in the Biodiversity2Drugs consortium.

This is a full-time, temporary position for two years under the central collective agreement. The starting date is January 1, 2027, or as agreed. The position is based in Uppsala. The appointment may be subject to security vetting, which applicants must pass if conducted.

Requirements

• PhD in computational chemistry, or a foreign degree equivalent to a PhD in computational chemistry; the degree must be obtained by the employment decision.
• Strong expertise in computational chemistry, with demonstrated experience in cheminformatics and structure-based ligand design.
• Proficiency in molecular docking or co-folding methods for predicting protein–ligand complexes.
• Experience working with chemical libraries.
• Excellent written and spoken English.
• Good collaborative abilities, motivation, creativity, and independence.

Nice To Haves

• Experience in machine learning.
• Experience in scientific programming.
• Experience in structure-based modeling of GPCRs and peptides.

Responsibilities

• Develop structure-based virtual screening techniques to identify ligands for peptide-binding GPCRs.
• Apply molecular docking and machine learning to screen peptide and peptidomimetic combinatorial libraries and collections of naturally occurring peptides.
• Collaborate with experimental research groups within the Biodiversity2Drugs consortium.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree