Role overview
In this applied role, you will use biological machine learning (ML), structural modelling, molecular simulations, and data science to generate, prioritise, and advance protein, antibody, and peptide candidates in live discovery programs. You will partner closely with wet‑lab teams to drive hypothesis‑led design and decision‑making across the design-make-test-analyse cycle.
Your responsibilities include:
- Apply and integrate computational tools (e.g., structure prediction, sequence design, molecular dynamics, developability and immunogenicity assessments, multi‑objective optimisation, de novo methods) 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 (e.g. AlphaFold2, Rosetta, ProteinMPNN, Ig-specific LMs, property predictors) for specific program needs; document decisions and performance vs. internal baselines
- Build robust, reusable design workflows and notebooks/pipelines for sequence generation, in silico mutagenesis, affinity maturation, humanization, and liabilities/developability triage
- Curate and analyse assay/sequence/structure data; perform error analysis; communicate clear, testable hypotheses and next‑step designs
- Collaborate with ML scientists and engineers within and outside of Digital Chemistry & Design (DCD) to productionise successful workflows; contribute practical requirements back to platform teams
- Work cross‑functionally with discovery biology, modality experts (e.g., peptides, antibodies, multi‑specifics), and other areas to balance potency, specificity, stability, manufacturability, and safety
This role emphasises applying and operationalising computational methods to generate impact in discovery. While it is not expected that the candidate is highly experienced in developing innovative ML solutions from scratch, they should be able to select, adapt, and rigorously evaluate state‑of‑the‑art methods and understand their assumptions and limits.
What we're looking for
- PhD (or equivalent) in Computational Biology, Bioinformatics, Structural Biology, Protein Engineering, Machine Learning, or related field; or Master’s degree with 3+ years of relevant experience. Candidates who have recently completed a PhD are encouraged to apply; research during PhD/postdoc counts as experience
- Demonstrated track-record applying computational methods to proteins/biologics (e.g. protein/antibody design, property prediction, structure‑based design, developability assessments), evidenced by publications, preprints, patents, open‑source, or project outcomes
- Solid understanding of protein sequence-structure-function and key therapeutic design trade‑offs (potency, specificity, stability, immunogenicity, PK/PD, manufacturability)
- Proficiency with Python and standard scientific/ML libraries (e.g. PyTorch/JAX/TensorFlow, NumPy/Pandas, RDKit/BioPython), and with tools such as AlphaFold2, Rosetta, ProteinMPNN, ESM family models, and MD packages
- Experience in usage of HPC and cloud solutions (AWS, Azure, or similar)
- Experience collaborating closely with experimental teams and using prospective assay data to drive design decisions
Experience within the following areas is a plus: antibody or protein engineering, multi‑objective optimisation for biologics, sequence library design or active learning, familiarity with laboratory workflows, screening formats, and data quality considerations in a pharma/biotech setting.
There is, of course, more on offer here than the uniqueness of our culture and the extraordinary results we produce. Being part of a global healthcare company means opportunities to learn and develop are all around us, while our benefits are designed with your career and life stage in mind.
Contact
For further information, please contact Paolo Marcatili ([email protected]).
Deadline
25 March 2026.
Please note that applications will be reviewed continuously, and interviews will be planned as soon as a suitable candidate is identified.
To ensure a fair recruitment process, please refrain from adding a photo in your CV.
We commit to an inclusive recruitment process and equality of opportunity for all our job applicants.
At Novo Nordisk, we're not chasing quick fixes – we're creating lasting change for long-term health. For over 100 years, we've been driven by a single purpose: to defeat serious chronic diseases and help millions of people live healthier lives. This dedication fuels our constant curiosity and inspires us to push the boundaries of what's possible in healthcare. We embrace diverse perspectives, seek out bold ideas, and build partnerships rooted in shared purpose. Together, we're making healthcare more accessible, treating and preventing diseases, and pioneering solutions that create change spanning generations. When you join us, you become part of something bigger – a legacy of impact that reaches far beyond today.