Helmholtz Zentrum München
1 week ago
MSCA Doctoral Network PhD position: Bioinformatic- and machine-learning-based search for new β-catenin peptide binders Helmholtz Zentrum Munich in Germany
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Oct 31, 2026
Country
Germany
University
Helmholtz Zentrum München
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About this position
PhD opportunity in bioinformatics, machine learning, and structural modelling of β-catenin peptide binders at Helmholtz Zentrum München. This MSCA Doctoral Network position focuses on the discovery of new β-catenin-binding peptides by combining proteome-wide bioinformatic screening, machine-learning model development, and structural prediction/refinement.
The project is centred on intrinsically disordered regions (IDRs) and their sequence features that enable interaction with β-catenin. The doctoral researcher will quantify common and overrepresented motifs in known β-catenin-binding IDRs, use these features to query the proteome, and develop models for IDR/β-catenin complex formation. A key component of the work is the FAIDR framework, using expectation-maximization and regularized logistic regression to distinguish known binders from the rest of the proteome. As experimental data become available, the models will be retrained and refined to improve predictive performance.
In parallel, the project includes structural modelling of known and putative binders using AlphaFold Multimer and related tools, including foundation models such as Boltz-1 and Chai-1, with possible further refinement by Rosetta FlexPepDock. Known β-catenin peptide interface structures will help template initial models, and high-scoring predictions will be evaluated using actifPTM to capture key interface features and improve model optimisation. The work contributes directly to a broader research programme that links in-silico screening with experimental validation and the design of novel β-catenin binders.
This position is hosted by Helmholtz Zentrum München and is part of a Horizon Europe / MSCA Doctoral Network (Grant Agreement No. 101311592). Salary follows the DFG scheme. The project includes a planned secondment at AMC for four months, with supervision by Dr. Nicolas Leveille, focused on bioinformatics and machine learning with cell-based data.
Eligible applicants must hold, or soon complete, a relevant science Master’s degree with excellent results, must not already hold a PhD, and must satisfy MSCA mobility rules. Excellent English communication skills are required. Applications are assessed on eligibility and scientific quality, followed by interview for shortlisted candidates.
Application deadline: 31 October 2026. Start window: January 2027 to March 2027.
Funding details
Available
What's required
Applicants of any nationality are welcome. Applicants must not already hold a doctoral degree and must hold, or shortly complete, a science Master’s degree with excellent results, meeting admission requirements for the doctoral programme at the host institution. Candidates must satisfy MSCA mobility rules and must not have resided or carried out their main activity in Germany for more than 12 months during the 36 months before recruitment. Excellent spoken and written English is required at minimum B2 level. Applicants should show motivation for multidisciplinary international doctoral research, hands-on experimental work, mandatory academic/industry secondments, publication, conference presentations, deliverables, and network-wide training and dissemination. Specific technical skills relevant to the project are expected.
How to apply
Apply exclusively through the Recruitment Portal at https://phd-recruiting.medunigraz.at/. Submit the motivation statement for the selected DC project, detailed CV with publication list if applicable, BSc/MSc diplomas and academic transcripts/supplements, and contact details for two referees. Shortlisted candidates will be invited to interview.
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