Domain: Structural bioinformatics; computational biology; methods development; machine learning

Keywords: protein sequence-based prediction; protein design; protein biophysics

Promotor: Wim Vranken

Starting date: 1st of September 2024, for a period of 3 + 1 years

Location: Bio2Byte group; (IB)2; VUB, Brussels, Belgium.

Funding: HORIZON-MSCA-2022-DN project PROHITS

In this Ph.D. project, you will provide relevant single protein level information for the genome scale metabolic models (GEMs) used in the project. To do so, you will be employing or developing methods to estimate the temperature dependence of Kcat of relevant enzymes for a range of thermophilic organisms. In addition, you will work on predicting the stability and unfolding of thermophilic proteins in their in vivo cellular context, by using existing data as well as Thermal Proteome Profiling data from mass spectrometry experiments in the project. Such approaches should aid the design of proteins that can operate at high temperature within their in vivo context, for example modifying mesophilic enzymes that catalyse specific industrially useful reactions not seen in thermophiles.

Besides the work in Brussels, you will spend a 3 month secondment at the University of Vienna (Vienna, Austria) to work on connecting the single protein information you generate to the GEM for the thermophile Sulfolobus acidocaldarius that will be developed there.

The project is part of a computational/experimental EU MSCA-DN project with a total of 10 Ph.D. students, and is highly interdisciplinary. Good programming skills (preferentially Python and/or C++) are essential, with knowledge of machine learning/artificial intelligence very desirable, and skills in discrete mathematics and statistics appreciated. Background knowledge of (structural) biology is a bonus. Candidates must be motivated to learn about all disciplines relevant to the project.

Candidates must be fluent in English.

Applications must be submitted online in English following the instructions and respecting the conditions at https://bit.ly/prohits. The deadline for applications is 15/03/2024 at 23:59 (CET)

Further general information about the PROHITS project: http://prohits.eu