Exogene is a VC-backed biotechnology startup using deep learning to unlock the discovery of innovative cell therapies for cancer treatment.
We are building a deep learning platform to rapidly identify specialised molecules that can guide immune cells within cancer patients to destroy cancer cells. The platform is trained on massive proprietary wet-lab datasets we generate in-house. Our mission is to discover cell therapies for untreatable solid tumours using a hybrid wet-lab/computational approach.
We are a remote-first company with labs at the BioEscalator in Oxford, UK.
As a machine learning scientist, you will build a best-in-class deep learning model tackling one of the most important open problems in immunology. You will build a model predicting the interaction between T-cell receptors (TCRs) and cancer cells using protein sequences and 3D protein structures as inputs. We generate the training data in-house at our labs.
A bit of background: TCR-based cell therapies are a new class of cancer therapies that can cure solid tumours (e.g. skin cancer, lung cancer). They consist of immune cells, known as T cells, that are extracted from patients, reprogrammed with an anti-cancer TCR and reintroduced into patients to destroy cancer cells.
Some cancer patients naturally produce anti-cancer TCRs, and these can be leveraged to develop effective cell therapies for millions of other patients. However, these TCRs are rare and difficult to identify using current technologies in the lab that have limited screening scalability. The models you will develop will enable rapid identification of anti-cancer TCRs at an unprecedented scale, and unlock the discovery of effective cell therapies to treat cancer.
You will work with our CTO to build the model, and with our R&D team and our commercial partners to set the direction of our in-house data generation pipeline. As the data science team grows in the next 12 months, you will have the opportunity to lead and manage additional team members to expand our modelling capabilities.
This is an exciting opportunity to work at the cutting-edge of both machine learning and immunology in an experienced and rapidly growing inter-disciplinary team.
You will be able to work remotely from anywhere, or from our labs in Oxford.
- 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 be in close contact with the founders, our lab-based R&D team and our commercial partners to shape our in-house data generation process by identifying blind spots in the data.
- 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 Required
- PhD in Machine Learning, Computer Science, Bioinformatics or related fields with 2+ years of relevant industry experience. Alternatively, MSc with 5+ years of relevant industry experience.
- Hands-on experience with cutting-edge machine learning techniques for natural language processing and image classification (e.g. transformers, self-supervised learning, transfer learning).
- Excellent software engineering skills.
- Excellent interpersonal and communication skills, both written and verbal – able to communicate technical information to a non-specialist audience.
- Curiosity to learn advanced concepts in biology.
Nice To Have
- Prior experience with bioinformatic techniques to analyse DNA sequencing datasets.
- Publications in top machine learning conferences/journals (e.g. KDD, ICML, NIPS).
- Prior experience with 3D structural modelling of proteins.
- Prior experience with cloud platforms (e.g. GCP or AWS).
What We Offer
- A passionate, inter-disciplinary team working at the cutting-edge of machine learning, immunology, biophysics and cell biology.
- The opportunity to have a positive impact on the health of millions of people worldwide.
- A lot of data nobody else has.
- Fully remote job, even after the pandemic will be over. You can of course work from our Oxford labs if you prefer.
- Stock options plan.
How To Apply
- Please send your CV and a cover letter (max 400 words) to email@example.com.
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, gender, disability, age, sexual orientation. We are proud to be an equal opportunities employer.
To apply for this job email your details to firstname.lastname@example.org