Machine Learning Scientist

About Exogene

Exogene is a techbio startup dedicated to revolutionising cancer treatment. We are committed to creating innovative therapies to combat solid tumours by harnessing the power of artificial intelligence (AI) and specialised laboratory screening methods. Utilising generative AI, we are uncovering new T-cell receptors (TCRs) with the potential to precisely target and eliminate cancer cells in the body.

We are backed by an impressive roster of investors, including Selvedge Venture, LifeArc Ventures, R42 Group, KQ Labs, and Entrepreneur First, among others.

While we are strong proponents of remote work, we also boast state-of-the-art laboratories located at the BioEscalator in Oxford, UK.

Job Description

We are seeking a dedicated Machine Learning Scientist to contribute to building best-in-class deep learning models aimed at solving one of the most critical challenges in immunology. You will be at the forefront of creating a model to discover novel cancer-specific T-cell receptors (TCRs) using a mix of protein sequences and 3D protein structures. Our lab at Oxford BioEscalator can generate training data in-house and validate our model’s predictions using cutting-edge TCR screening technologies.

TCR-based therapies represent a groundbreaking class of cancer treatments with the potential to cure solid tumours, such as skin and lung cancer. These therapies involve genetically reprogramming the immune system to use novel T-cell receptors (TCRs) to detect and kill cancer cells. The models you will develop facilitate the rapid discovery of novel anti-cancer TCRs at an unprecedented scale.

Compared to traditional radiotherapy and chemotherapy, which have harmful side effects and can damage healthy tissues, TCR-based therapies are more targeted and less toxic as they direct the immune system to attack only cancer cells. Moreover, since they involve a reprogramming of the immune system, these therapies have the potential to unlock a long-lasting, anti-cancer immune response and reduce the likelihood of cancer recurrence.

This position offers a unique opportunity to work at the intersection of machine learning and immunology with a seasoned and rapidly expanding inter-disciplinary team. You have the flexibility to work remotely from anywhere.

Responsibilities

  • You will develop models to predict the interaction between TCRs and peptide-HLA complexes on the surface of cancer cells, using massive heterogeneous biological datasets (e.g. protein sequences and 3D protein structures).
  • You will build generative models to generate novel, high-affinity TCRs.
  • You will be up-to-date with the most relevant machine learning research.
  • You will contribute to manuscripts for peer-reviewed publications.

Skills and Qualifications

  • MSc in Machine Learning, Computer Science, Bioinformatics or related fields with 2+ years of relevant industry experience.
  • Hands-on experience with cutting-edge machine learning techniques (LLMs, transformers, diffusion models).
  • Excellent software engineering skills (Python).
  • Excellent interpersonal and communication skills, both written and verbal – able to communicate technical information to a non-specialist audience.
  • A strong desire to learn advanced biology concepts.

Nice to have

  • Experience with 3D protein structural modelling (e.g. AlphaFold2, RFDiffusion) and visualisation tools (e.g. PyMOL).
  • Familiarity with cloud platforms (e.g., GCP or AWS).
  • Publications in top machine learning conferences/journals (e.g., KDD, ICML, NIPS).
  • Previous experience with bioinformatic techniques for analysing next-generation DNA sequencing datasets.

What We Offer

  • A passionate, dynamic and inter-disciplinary team working at the cutting-edge of machine learning and immunology.
  • The opportunity to make a meaningful impact on the health and well-being of millions of people worldwide.
  • Access to unique training data unavailable elsewhere.
  • A fully remote job, with the option to work from our Oxford labs if preferred.
  • A competitive stock options plan.

How to apply

Please send your CV and cover letter (max 400 words) to info at exogene.co.uk 

Equal Opportunities Employer

At Exogene, we believe in getting as many points of view as possible – we support and celebrate diversity in our workforce, and we hire and promote regardless of race, religion, colour, national origin, sex, disability, age, sexual orientation. We are proud to be an equal opportunities employer.