PhD Position - AI Models for Membrane Protein Design

We are seeking a motivated and creative PhD student to develop the next generation of AI-driven protein design methods that explicitly account for protein–lipid and protein–membrane interactions. The research will involve training machine-learning models on large structure and sequence datasets and integrating membrane-specific biophysical constraints to enable the design of membrane proteins and nanopores. These methods will open the door to engineering sophisticated functionalities into synthetic membrane proteins - including selective transport, sensing, and signal transduction.

Research environment

The laboratory of Dr. Anastassia Vorobieva at the VIB–VUB Center for Structural Biology (co-affiliated with the VIB Center for AI & Computational Biology) pioneers methods for the de novo design of transmembrane β-barrel nanopores. The group provides a highly interdisciplinary environment where computational method development is closely integrated with experimental validation. The successful candidate will have opportunities to collaborate with researchers in protein engineering, structural biology, and nanopore technologies, obtaining direct feedback on the tools they develop.

The VIB–VUB Center for Structural Biology offers access to state-of-the-art infrastructure including cryo-electron microscopy, X-ray crystallography, NMR spectroscopy, and high-performance computing. The Vorobieva laboratory is an active member of the international RosettaCommons community, which provides opportunities for collaboration, training, workshops, and networking with leading researchers in computational protein design.

Your profile

We are looking for an enthusiastic researcher with a strong interest in computational biology, protein design, and AI applied to structural biology. The ideal candidate should enjoy interdisciplinary work, thrive in a collaborative international environment, and be motivated to contribute both independently and as part of a team.

Essential qualifications

• Master's degree (or equivalent) in Computational Biology, Bioinformatics, Computer Science, AI/Machine Learning, Physics, Mathematics, Bioengineering, Structural Biology, Biophysics, or a related field
• Strong quantitative, analytical, and problem-solving skills
• Programming experience in Python or a similar scientific language
• Interest in machine learning and data-driven modelling
• Excellent written and spoken communication skills in English
• Ability to work both independently and collaboratively in an international research setting

Desirable qualifications

Experience in any of the following areas will be considered an advantage:

• Deep learning or machine learning
• Structural bioinformatics
• Protein structure prediction and modelling
• Molecular simulations
• Membrane proteins or membrane biophysics
• Scientific software development
• Linux and high-performance computing environments
• Rosetta or related protein design software

Our offer

• A fully funded PhD position with an attractive salary. 
• A dynamic, highly stimulating, and interdisciplinary research environment in a top research institute 
• Access to state-of-the-art facilities and infrastructure
• An international, supportive lab culture