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. You'll 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