The position

The human genome contains many non-canonical, cryptic open reading frames whose peptide products fall outside standard protein reference catalogs. Some of these cryptic ORF-derived peptides are nonetheless presented at the cell surface by HLA-I molecules and can serve as tumor antigens, but how such low-abundance peptides are generated and how they compete for HLA-I presentation, particularly in cancers such as melanoma, remains poorly understood, and predicting which of them achieve stable presentation is an open problem.

This project will elucidate how low-abundance cryptic ORF-derived peptides compete for HLA-I presentation in melanoma. Using advanced immunopeptidomics in patient-derived melanoma cell lines, it identifies cryptic HLA-I peptides, quantifies their stability and turnover, and builds an integrative machine-learning model that predicts cryptic peptide presentation. It sits within ORFeus Work Package 3, which investigates the roles of the dark proteome in cancer and immunology, and it draws on data from across the network, including translation evidence from ribosome profiling and secreted-microprotein and regulatory inputs that expand the model's training data.

Main tasks

● Identify cryptic HLA-I peptides in around 20 patient-derived primary melanoma cell lines using advanced immunopeptidomics, cross-validating against rare translation events from the projects of other doctoral candidates (DCs) in the network, here DC3.

● Quantify the stability and turnover of these peptides using SILAC pulse-chase assays under a range of cellular perturbations.

● Develop an integrative machine-learning model that predicts cryptic peptide presentation, synthesizing data streams from across the network, including translation features, immunopeptidomics data, and secreted-microprotein sources from DC5, together with regulatory insights from DC14 and cryptic peptides from DC11 and DC13.

● Collaborate across the ORFeus network, contribute methods and results to the shared ORFeome platform, and produce the project's scientific report.

Methods and platforms: advanced immunopeptidomics (including timsTOF Ultra2 mass spectrometry and data-independent acquisition), deep-learning spectrum prediction, SILAC pulse-chase assays for peptide stability and turnover, and integrative machine learning for peptide-presentation prediction, working with patient-derived melanoma cell lines and consortium datasets via the ORFeome platform.

Secondment: you will spend around three months at an industry partner, integrating findings on cryptic peptides into mRNA-based vaccine development pipelines. You will also be guided by an independent academic advisor, with the possibility of a short, primarily virtual research exchange to strengthen the project.

Your profile

MSCA eligibility

You must meet all of the following on your recruitment date:

● You do not already hold a doctoral degree. If you have defended a doctoral thesis but the degree has not yet been formally awarded, you are not eligible.

● Mobility rule: you must not have lived or carried out your main activity (work, studies, and so on) in Switzerland for more than 12 months in the 36 months immediately before your recruitment date. Compulsory national service, short stays such as holidays, and time spent in a procedure to obtain refugee status under the Geneva Convention do not count toward the 12 months.

● You hold, or will hold before the start date, a degree that formally entitles you to enroll in a doctorate, and you can enroll in the doctoral program at the University of Lausanne.

Candidates of any nationality may apply. There is no limit on prior research experience, as long as you do not already hold a doctorate.

Project-specific profile

● A master's degree (or equivalent) in immunology, molecular biology, biochemistry, proteomics, bioinformatics, or a related life-science field.

● Desirable: experience with SILAC-based mass spectrometry methods and machine learning, and an interest in cancer antigens, cryptic peptides, and the dark proteome.

● Good written and spoken English.

● Motivation for interdisciplinary, collaborative research, and willingness to travel for the secondment and network events.

What we offer

A full-time employment contract for 36 months as a salaried researcher, with full social security coverage, under the rules of the Marie Skłodowska-Curie Actions. This is a paid employment contract, not a stipend or scholarship.

The salary has a living allowance and a mobility allowance, plus a family allowance if you have family obligations when you are recruited. The indicative gross salary for this position is 4’583.33 CHF per month. This is what you are paid before income tax and your own social-security contributions are deducted.

Beyond salary, you will receive:

● Supervision by a world-leading, interdisciplinary supervisory team.

● A secondment of around three months with an ORFeus industry partner.

● A structured training program: network-wide schools, transferable-skills training, workshops, and international conferences.

● Enrollment in a doctoral program leading to a PhD.

● UNIL provides eligible employees with occupational pension coverage (LPP), paid annual leave, paid public holidays and other benefits in accordance with UNIL regulations.

Duration and funding beyond the MSCA contract

The MSCA employment contract covers 36 months of full-time, fully funded employment. In line with the host institution's doctoral policy, the host will provide funding to support completion of the doctorate in the fourth year as continued employment at the standard doctoral salary scale; terms confirmed at offer stage.

Working at the University of Lausanne

The University of Lausanne is a leading international teaching and research institution, with over 5,000 employees and 17,000 students split between its Dorigny campus, CHUV and Epalinges. As an employer, UNIL encourages excellence, individual recognition and responsibility. At UNIL, the Department of Fundamental Oncology includes numerous fundamental and translational research groups. It is also home to the Lausanne Branch of the Ludwig Institute for Cancer Research. The department's scientific mission is to carry out state-of the art research in tumor microenvironment and onco-immunology and to further therapeutic development in the fields of T cell engineering, cancer immunotherapy, and precision oncology. Its ultimate goal is to drive discovery to develop transformative care for cancer patients.

You will join the group of Prof. Michal Bassani-Sternberg, which develops advanced immunopeptidomics and machine-learning methods to characterize HLA peptide presentation and identify cancer antigens, including cryptic ORF-derived peptides. You will work closely with the group of Prof. Uwe Ohler at the Max Delbrück Center, who brings complementary computational-biology and translation-modeling expertise. You will enroll as a PhD candidate at Doctoral School of the Faculty of Biology and Medicine at the University of Lausanne.