relationrx - Senior Data Scientist – Rosalind (DNA Sequence Modelling & Computational Genomics)
Requirements
• PhD in genomics, computational biology, bioinformatics, or a related quantitative discipline. • Post-PhD experience, ideally including time in an industry, biotech, or pharmaceutical environment. • Experience with DNA language models, genomic foundation models, or transformer-based sequence models. • Knowledge of statistical fine-mapping, colocalisation, eQTL analysis, and linking genetic signals to effector genes. • High proficiency in Python (preferred) and R, with experience working in high-performance computing environments. • Ability to operate independently, driving projects from concept through delivery. • Familiarity with single-cell transcriptomics or patient-derived datasets. • Experience working in interdisciplinary teams within biotech or pharma settings. • A background in statistical modelling and algorithm development. • Experience integrating sequence models with single-cell and perturbation datasets. • Familiarity with 3D genome / chromatin interaction data where relevant (Hi-C, Capture-C, etc.). • PERSONALLY, YOU ARE • Clear communicator. • Driven by impact. • Humble and hungry to learn. • Motivated and curious. • Impact-driven and passionate about improving patient outcomes. • Comfortable working in dynamic, fast-paced environments. • Relation is a committed equal opportunities employer. • RECRUITMENT AGENCIES • Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs.
Responsibilities
• Develop and implement computational methods to model DNA sequence, regulatory elements, and genetic variation in disease-relevant contexts. • Build and evaluate models for sequence-to-function tasks such as variant effect prediction, regulatory activity prediction, and the interpretation of non-coding disease signals. • Integrate DNA-derived features with transcriptomic, epigenomic, and perturbational datasets to uncover disease mechanisms and support target prioritisation. • Partner closely with experimental and machine learning researchers to validate hypotheses, interpret results, and guide downstream studies. • Communicate findings clearly to internal stakeholders, including presenting methods, results, and recommendations. • Contribute to publications, scientific communications, and project documentation, supporting scientific excellence and external visibility. • PhD in genomics, computational biology, bioinformatics, or a related quantitative discipline. • Experience with DNA language models, genomic foundation models, or transformer-based sequence models. • Knowledge of statistical fine-mapping, colocalisation, eQTL analysis, and linking genetic signals to effector genes. • High proficiency in Python (preferred) and R, with experience working in high-performance computing environments. • Ability to operate independently, driving projects from concept through delivery.
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