Lead Scientist - Large Molecules

A large molecule specialist to bring deep domain knowledge in antibody engineering, structural biology, and biologics to define the scientific workflows and modeling strategy for antibody-antigen co-folding, binder prediction, and developability prediction. You'll give large molecules a real point of ownership at Apheris, deciding what's scientifically relevant as the network grows, and partnering with ML and engineering teams who own the actual model-building.

What you'll do

• Define the scientific workflow, evaluation strategy, and benchmarking approach for our large molecule programs, including antibody-antigen co-folding, binder prediction, and antibody developability
• Use our own product as a hands-on user, and define user requirements for large molecule workflows so what gets built actually matches how scientists work
• Drive adoption of our large molecule models with pharma partners - helping them identify which programs and use cases they should be applied to, and supporting them in getting real value out of them
• Translate scientific and biological requirements from pharma partners into concrete inputs the ML/engineering team can build against
• Review model outputs and evaluation results against real structural biology / antibody engineering knowledge, flagging where something doesn't hold up biologically
• Represent Apheris's scientific perspective in partner conversations across our large molecule networks — aligning on objectives, evaluation criteria, and data requirements

What you'll need

• PhD, MSc, or equivalent experience, plus 5+ years in structural biology, antibody engineering, immunology, protein engineering, or a related biologics discipline
• Real hands-on experience in antibody design, developability, or binder discovery
• Exposure to applying AI/ML to biological problems; you don't need to build models yourself, but understand them well enough to contribute to a modeling workflow and judge whether outputs make sense
• Comfortable partnering closely with ML/engineering teams and translating between biological reasoning and technical implementation
• Clear communication across scientific and technical audiences, and with pharma partner stakeholders

Nice to have

• Familiarity with OpenFold, AlphaFold, Boltz, or similar structure prediction tools
• Experience with antibody developability assays, immunogenicity, or biologics manufacturability
• Worked directly with pharma partners or in a consortium/collaborative research setting
• Publication record in structural biology, immunology, or antibody engineering

What they offer

• Competitive compensation with early-stage virtual share options
• Remote-first, with flexibility on work location
• Wellbeing support: mental health resources, work-from-home budget, co-working stipend, learning budget
• Generous holiday allowance
• Optional office days at Berlin HQ or another European location