d) - Immunopeptidomics & Antigen Discovery

GSK•Heidelberg, MS

About The Position

At GSK, we have bold ambitions for patients, aiming to positively impact the health of 2.5 billion people by the end of the decade. Our R&D focuses on discovering and delivering vaccines and medicines, combining our understanding of the immune system with cutting-edge technology to transform people’s lives. GSK fosters a culture ambitious for patients, accountable for impact, and committed to doing the right thing, making sure that we focus our efforts on accelerating significant assets that meet patients’ needs and have the highest probability of success. We’re uniting science, technology, and talent to get ahead of disease together. Find out more: Our approach to R&D Computational Biologist / Principal Scientist (m/f/d) - Immunopeptidomics & Antigen Discovery We are seeking a highly motivated Computational Biologist / Principal Scientist (m/f/d) specialising in Immunopeptidomics and Computational Proteomics with experience in mass spectrometry data analysis, peptide identification, and machine learning. This role will be a key contributor alongside a team of talented computational biologists and experimental scientists in the Oncology Translational Research Department. The Scientist will be responsible for developing and optimising computational pipelines to identify MHC-I presented peptides to support precision immunotherapy programs.

Requirements

PhD in Computational Biology, Bioinformatics, Proteomics, or related field.
Extensive experience in mass spectrometry data analysis and peptide identification (MaxQuant, PEAKS, MSFragger).
Proficiency in R or Python programming with experience in bioinformatics pipeline development.
Strong statistical and machine learning skills.
Ability to communicate with team members from different backgrounds, as well as senior members of the research units.
Ability to deliver high quality, consistent results in a timely fashion with a positive can-do and result-oriented attitude.

Nice To Haves

Multiple years of postdoctoral or industry experience in computational proteomics or immunopeptidomics.
Experience with non-canonical peptide discovery and MHC binding prediction tools (NetMHCpan, MHCflurry).
Excellent leadership and communication skills, with a track record of building and leading high-performing teams.

Responsibilities

Lead the development and optimisation of computational pipelines for large-scale immunopeptidomics data analysis from mass spectrometry (LC-MS/MS); building and maintaining workflows in Python and R.
Integrate immunopeptidome data with patient-matched whole-genome sequencing (WGS) and RNA-seq data to build predictive models for MHC-I binding affinity.
Collaborate closely with the Oncology Translational Research team members, immunologists, and clinical teams to translate complex data into actionable insights for drug discovery.
Derive insights from complex immunopeptidomics data and report to relevant stakeholders to a high quality and within defined timeframes.

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