This role should strengthen our Discovery and Preclinical teams by combining structural biology, computational tooling, and AI/ML assisted feature predictions to accelerate and improve our antibody development
Job Summary
This role should strengthen our Discovery and Preclinical teams by combining structural biology, computational tooling, and AI/ML assisted feature predictions to accelerate and improve our antibody development.
Key responsibilities include identifying, evaluating, and implementing computational structural biology tools, interpreting structural data, and supporting wet-lab colleagues with interpretation of structural predictions.
The company offers the opportunity to establish a new role within the organization, contributing to shaping its future direction, along with a competitive salary package with extensive benefits.
Matching Summary
This role should strengthen our Discovery and Preclinical teams by combining structural biology, computational tooling, and AI/ML assisted feature predictions to accelerate and improve our antibody development.
Skills & Requirements
Must-have
Structural computational biology tools
Protein structure prediction and design
Python skills and reproducible workflows
Git, testing, and collaborative development
Structure-based antibody engineering
Developability predictions
Nice-to-have
Molecular dynamics simulations experience
FAIR data principles familiarity
AI and machine learning concepts
Proactive and curious mindset
Bridging computation and experimentation
Key Requirements
PhD in Structural Biology, Computational Biology, Biophysics, or related field
Strong background in structural modelling and analysis
Programming proficiency (Python)
Workflow automation experience
Hands-on experience with containerization technologies (Docker, Podman)