MSCA Doctoral Network PhD position: Bioinformatic and Machine Learning Search for New β-Catenin Peptide Binders

This PhD position is part of the MSCA Doctoral Network at the Technical University of Vienna, focusing on the bioinformatic and machine-learning-based identification of new β-catenin peptide binders. The project aims to quantify elements in intrinsically disordered regions (IDRs) that bind to β-catenin and develop predictive models for screening potential binders. Candidates will engage in both computational modeling and experimental validation, contributing to a collaborative research environment. Applicants are expected to have a strong background in relevant fields and a commitment to advancing knowledge in biochemistry.

• Quantify common elements in IDR sequences that bind to β-catenin.
• Develop protocols for modeling IDR/β-catenin complexes.
• Utilize machine learning algorithms to isolate distinguishing sequence features.
• Predict potential β-catenin IDR binders for proteome-wide screening.
• Refine predictive models based on experimental data.
• Conduct structural modeling of known and predicted binders using advanced software.
• Collaborate with team members on experimental validation of predictions.