Protein Design Data Scientist — ML & Protein Interactions

Genmab; København; Hybrid; DKK 445,000 - 668,000; Full time

Benefits offered by this job

Pension

Health insurance and wellness benefits

Paid time off

Employee support programs

Job summary

Genmab is seeking a Data Scientist with a strong machine learning background in protein structure modelling to join our Discovery Data Science team in Utrecht. You will work at the interface of ML, molecular modelling, and experimental antibody discovery to design and evaluate potential antibody binders against therapeutic targets.

You will analyze target structures, apply generative design models, and develop workflows to filter and prioritise computational designs, while collaborating with

Qualifications

• PhD in computational biology or a related field with hands-on ML applied to protein structures.
• Hands-on ML experience with protein structures or protein–protein interactions.
• Strong written and spoken English communications.

Responsibilities

• Analyse protein structures and potential binding surfaces for de novo binder design.
• Benchmark generative ML models for protein complexes and assess performance.
• Develop workflows to filter, rank, and prioritise designs for experimental testing.
• Collaborate with lab scientists to interpret molecular data and refine designs.
• Write robust Python code following best practices and version control.
• Contribute to reproducible scientific software and workflows.

Skills

Python programming

Machine learning

Protein modelling

Team collaboration

English communication

Education

PhD in Computational Biology or related

PhD nearing completion welcome

Tools

Git

Linux command line

HPC/Cloud

Jupyter

Job description

Genmab is seeking a Data Scientist with a strong machine learning background in protein structure modelling to join our Discovery Data Science team in Utrecht. You will work at the interface of ML, molecular modelling, and experimental antibody discovery to design and evaluate potential antibody binders against therapeutic targets.

You will analyze target structures, apply generative design models, and develop workflows to filter and prioritise computational designs, while collaborating with