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