Computational Biologist – Immuno-Oncology Overview: This is a unique opportunity for a driven computational biologist to shape the future of antigen discovery in a cutting-edge biotech environment. Youll play a key role in the development of unsupervised machine learning models using transcriptomic datasets to support target identification and product development. As the team grows, this position offers a clear path into leadershiP, ideal for someone ready to expand their impact both scientifically and strategically. Key Responsibilities: Develop and refine unsupervised machine learning approaches to analyse multi-omics data, with a focus on transcriptomics Collaborate closely with experimental scientists and bioinformaticians to integrate data and guide research direction Support internal and external teams with in-house tools such as CrytoMAP and BamQuery Contribute to antigen discovery pipelines and help define computational strategy Help grow and mentor the computational biology function as the team expands Stay current with emerging methods in computational immunology, machine learning, and applied bioinformatics Ideal Background: PhD in Computational Biology, Bioinformatics, Machine Learning, or a related field Strong experience with multi-omics data integration, ideally within immunology or oncology Hands-on expertise in Python and/or R, and familiarity with common bioinformatics workflows Track record of developing ML-based models, in an unsupervised context Excellent problem-solving, communication and collaboration skills Experience in a biotech or translational research setting is highly desirable