Description:
We are currently seeking talented scientists to join our team in Oxford, UK, with a focus on combining antibody development knowledge and Machine Learning expertise.
Key Responsibilities
- Develop innovative and creative solutions to design novel antibodies or nanobodies in collaboration with other departments.
- Utilize sequence, structure, and machine learning-driven modeling approaches to enhance functional and biophysical properties of active pharmaceutical ingredients (APIs).
- Collaborate effectively with team members to achieve project goals and implement best-performance techniques into production.
- Implement and advance state-of-the-art Molecular Modelling and/or Machine Learning technologies in antibody design, accelerating and innovating the drug discovery process at Novo Nordisk, acting as a critical component of project progress. Generate and store ML-ready data from antibody projects.
- Identify potential liabilities and developability issues throughout the antibody discovery pipeline.
Qualifications
To excel in this role, you should possess:
- A Master's degree (PhD preferred) in Computational Biology, Bioinformatics, Machine Learning, or a related field.
- At least 3 years of experience in clinical or industrial antibody/nanobody development or equivalent academic accomplishments. More experienced scientists are also encouraged to apply.
- In-depth understanding of antibody or nanobody sequence, structure, function, and their development in an industrial setting.
- Solid expertise in relevant computational tools, including Python programming, molecular modeling and simulations (Rosetta, Schrödinger, or similar), sequence analysis, and machine learning frameworks (PyTorch, Azure ML, or similar).
- Experience in utilizing HPC solutions (AWS, Azure, or similar).