Novo Nordisk is looking for a Data Scientist to join our biologics discovery efforts. You will apply computational methods to design next-generation biologics for obesity and chronic diseases, working at the intersection of biological machine learning, structural modelling, and data science.
What You'll Do
- Apply and integrate computational tools such as structure prediction, sequence design, molecular dynamics, and developability assessments to design and prioritise biologics candidates.
- Lead prospective design campaigns in partnership with protein engineering and assay teams; drive design-make-test-analyse cycles and iterate based on experimental feedback.
- Select, configure, and benchmark models and workflows for specific program needs; document decisions and performance versus internal baselines.
- Build robust, reusable design workflows and pipelines for sequence generation, in silico mutagenesis, affinity maturation, humanization, and developability triage.
- Curate and analyse assay, sequence, and structure data; perform error analysis; communicate clear, testable hypotheses and next-step designs.
- Collaborate with ML scientists and engineers to productionise successful workflows; contribute practical requirements back to platform teams.
- Work cross-functionally with discovery biology and modality experts to balance potency, specificity, stability, manufacturability, and safety.
What We're Looking For
- PhD (or equivalent) in Computational Biology, Bioinformatics, Structural Biology, Protein Engineering, Machine Learning, or a related field; or a Master’s degree with 3+ years of relevant experience.
- Demonstrated track-record applying computational methods to proteins or biologics, evidenced by publications, preprints, patents, open-source contributions, or project outcomes.
- Solid understanding of protein sequence-structure-function and key therapeutic design trade-offs such as potency, specificity, stability, immunogenicity, PK/PD, and manufacturability.
- Proficiency with Python and standard scientific/ML libraries, and with tools such as AlphaFold2, Rosetta, ProteinMPNN, ESM family models, and molecular dynamics packages.
Technical Stack
- Languages & Core Libraries: Python, PyTorch/JAX/TensorFlow, NumPy/Pandas, RDKit/BioPython
- Key Tools & Platforms: AlphaFold2, Rosetta, ProteinMPNN, ESM family models, MD packages
Team & Environment
You will join the In Silico Biologics Discovery team within the Digital Chemistry & Design and AI & Digital Innovation areas.
Work Mode
This is an onsite position located in Måløv, Denmark.
We value a diverse and inclusive culture, where our team members can thrive and grow. Our team consists of passionate, goal-oriented individuals who take pride in their work and are committed to making a difference in patients' lives.
