Machine Learning Scientist – Sequence Modelling
Core
Design and apply advanced machine learning techniques to DNA and genetic data to uncover associations between genetic variants and diseases.
Role type
Senior IC machine learning scientist (genomics/sequence modelling)
Builds
Production ML models for variant interpretation, gene discovery, and regulatory modelling
Domain
Biotech / Genomics / Drug Discovery
Deliverable
production ML models
Required skills
Machine learning, DNA sequence modelling, Python, PyTorch or TensorFlow, variant interpretation, gene discovery, regulatory modelling, large-scale dataset handling, robust model evaluation
Preferred skills
Transformers in biomedical research, lab-in-the-loop frameworks, representation learning for DNA
Technologies
PyTorch, TensorFlow
Responsibilities
Develop and apply sequence modelling ML techniques to DNA sequences; Train, fine-tune and evaluate DNA sequence models for variant interpretation, gene discovery and regulatory modelling; Collaborate with computational and experimental scientists to generate and validate ML-driven hypotheses; Leverage large-scale external and internal datasets to build and adapt models for disease-focused applications; Design robust evaluations to measure model quality, biological relevance and translational value; Contribute to scientific innovation by applying the latest advances in machine learning and genomics.
Seniority
Senior, hands-on IC