Senior Scientist, Biologics Drug Discovery

The opportunity

Relation is offering an outstanding opportunity for an Senior Scientist, Biologics Drug Discovery to bring deep biologics drug discovery knowledge to our growing pipeline. You will contribute to target assessment, modality selection and biologics discovery strategies through deep technical expertise and hands‑on scientific execution from early concept through to IND‑enabling studies.

As Relation grows its scientific and machine learning capabilities, you will act as a highly experienced scientist, bringing deep expertise in antibody discovery and engineering while contributing directly to programme execution and scientific decision‑making, working alongside our computational, ML, and translational teams to translate biological insight into well‑designed molecules with a credible path to the clinic.

We are particularly interested in scientists who have personally designed, engineered and optimised antibody molecules, including experience with affinity maturation, CDR engineering, develop ability assessment and data‑driven molecule optimisation. You will additionally be a key technical voice in pipeline decisions and a trusted partner to colleagues across Drug Discovery and beyond.

• Demonstrated hands‑on experience designing, engineering and optimising antibody molecules, with a strong understanding of the experimental approaches used to assess potency, selectivity, develop ability and mechanism of action.

• Ability to independently interpret complex datasets and use those data to drive molecule design and optimisation decisions.

• Maintain a hands‑on role in biologics discovery activities while partnering closely with internal and external teams.

• Drive biologics programs end‑to‑end — from target validation and hit identification through lead characterization, optimisation, and develop ability triage — against agreed Target Product Profiles (TPPs).

• Make informed modality decisions across the biologics landscape (antibodies, bispecifics, ADCs, fusion proteins, fragments) and ensure the right molecule is selected for the right target and indication.

• Design and oversee fit‑for‑purpose discovery packages, combining cell‑based functional assays, biophysical characterization (SPR/Biacore, BLI/Octet), and develop ability assessment to drive sound candidate selection.

• Operate effectively in a matrixed pharma/biotech environment, partnering with Computational Biology, Machine Learning, CMC, DMPK, Toxicology, and Translational colleagues to de‑risk candidates and progress them toward IND‑enabling studies.

• Partner with external collaborators and CROs, contributing to study design, data review and scientific interpretation.

• Share expertise with colleagues and contribute to a collaborative scientific environment.

• Partner with our ML and computational biology teams to bring biologics drug discovery insight into how predictive and generative approaches are applied to target selection, molecule design, and lead optimisation.

• Personally contribute to the design, engineering and optimisation of antibody molecules, using experimental data to guide scientific decisions and progression strategies.

• Contribute to Relation’s scientific culture by mentoring junior scientists in biologics drug discovery, supporting publications and conference visibility, and helping to shape the broader scientific identity of the biologics group.

• A PhD. in Molecular Biology, Immunology, Pharmacology, Cell Biology, Protein Engineering, or a related life‑science discipline.

• Hands‑on drug discovery experience gained in a pharma or biotech setting, with a clear track record of contributing to biologics programmes progressing through key discovery milestones (target validation, hit‑to‑lead, lead optimisation, candidate selection).

• Proven experience working in a matrixed pharma/biotech environment, partnering effectively across functions (e.g. CMC, DMPK, Toxicology, Computational/ML, Translational) and balancing multiple stakeholders.

• Deep working knowledge of biologics drug discovery: how biology is translated into a molecule, how modalities are chosen, how discovery cascades are designed, and what…