Many cancers and other diseases are caused, or resist treatment, because T cells can't recognize or target cells correctly. We're progressing first-in-class antigen modulators through the clinic, developed to treat disease by controlling T cell activation. Our technology modulates antigen presentation, flicking a switch inside cells to alter their appearance to the immune system.
This approach marks a fundamental shift in how we treat people living with autoimmune disorders, cancers and infectious diseases.
Role Overview:
Due to ongoing growth, we are recruiting a Translational Data Scientist – the successful candidate will contribute to the overall conceptualisation, design and implementation of advanced statistical data analysis strategies to extract insights from temporal/time course omics’ data generated from Greywolf’s EMITT and EAST clinical trials. This includes, but is not limited to, the development of multivariate pharmacodynmic biomarkers for PK/PD, correlating to clinical outcomes and advancing understanding of mechanism.
This position is a highly collaborative role embedded within a cross-functional team where you will work closely with computational biologists, immunologists and translational scientists.
Core Responsibilities:
- Develop and apply statistical and machine learning methods (e.g linear mixed models, GAMMs/splines for non-linear dynamics) to derive and deliver key biological insights across multi-omic (TCR Sequencing, RNA Sequencing, Immunopeptidomics, Proteomics) longitudinal patient profiling.
- Develop multivariate biomarker methods to integrate with clinical outcomes and pharmacodynamic/pharmacokinetic modelling.
- Partner with research and translational colleagues to elucidate the mechanism of action by deriving inference from multi-modal data, directly generating hypotheses for reverse translational approaches.
- Partner with bioinformatics engineers to define analytical specifications and validate the scientific rigor of high-quality Nextflow pipelines.
- Synthesise high-dimensional data into clear, actionable insights and communicate technical, statistical and biological findings effectively to facilitate decision making within cross-functional asset teams.
- Actively engage with new technological and scientific advances in the field of quantitative immunology.
- Foster a collaborative culture while maintaining technical accountability with external CRO partners to ensure high-quality data generation.
Skills, Knowledge, Qualifications and Experience:
- PhD (or equivalent industry experience) in Computational Biology, Systems Immunology, Biostatistics, or a related quantitative discipline.
- Proven application and working theoretical knowledge of multivariate statistical methods to high-dimensional temporal/time-course datasets.
- Deep experience analysing high-dimensional datasets generated on sequencing or mass spectrometry technologies.
- Experience applying and making inference from machine learning methods (unsupervised and supervised).
- Expertise and fluency in at least one statistical programming language (E.g R, Python or Julia), with a strong focus on reproducible code standards.
- Demonstrated ability to articulate complex statistical insights to cross-functional teams (biologists, immunologists, clinicians) and influence decision-making.
What Sets You Apart:
- Understanding of antigen processing/presentation and T-cell receptor dynamics.
- Experience working with translational patient data.
- Proficient in Linux environments, with practical experience using containerisation (Docker) and executing workflows on cloud infrastructure (AWS) via workflow managers (Nextflow).
If you are passionate about data science and want to work in a fast growing, exciting company - we invite you to apply and join our mission of advancing ground-breaking discoveries.
(Some of..) our Perks and Benefits:
- 2 holiday office shut-down periods during July and December, in addition to 25 days annual holiday.
- Flexible, hybrid working (you should be able to attend our office in Milton Park, Oxfordshire 1-2 times per week and travel to partner sites, board and other meetings, as required).
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