VP Head of Therapeutics Design

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pbJob Title: /b VP head of Therapeutics Design /p pbJob Type: /b Permanent /p pbLocation: /bAbingdon
- UK, Alderley Park
- UK or Verona, Italy /p h3Our Company /h3 pEvotec is a leader in the discovery and development of novel small molecule drugs with operational sites in Europe and the US. The Company has built substantial drug discovery expertise and an industrialised platform that can drive new innovative small molecule compounds into the clinic. In addition, Evotec has built a deep internal knowledge base in the treatment of diseases related to neuroscience, pain, oncology, inflammation and metabolic diseases. Leveraging these skills and expertise the Company intends to develop best-in-class differentiated therapeutics and deliver superior science-driven discovery alliances with pharmaceutical and biotechnology companies /p h3Purpose of the role /h3 ul liThe Vice President, Head of Therapeutics Design is the single accountable owner of Evotec’s in silico therapeutics design capability, bringing computational chemistry, generative and modality design (small molecule, peptide, protein engineering, targeted degraders and molecular glues) and predictive ADMET/Safety together under one mandate. /li liThe role exists at the point where chemistry meets biology at scale. Evotec pairs deep computational chemistry with proprietary patient-derived multi-omics and real experimental safety and toxicology data, a combination that software-only and biology-only competitors cannot replicate. The role holder makes chemistry decisions demonstrably better by grounding them in that data, rather than competing in commoditising standalone generative design. /li liThis is a newly created unit within the In Silico AI group, and the role carries an explicit build mandate: set the technical vision, shape and grow the team,



and industrialise the capability. It comes with executive sponsorshipa consolidated AI and engineering capability to draw on, and a direct reporting line to the EVP, Head of Global In Silico AI. /li /ul h3Core accountabilities /h3 ul liSet and own the technical vision for therapeutics design across small molecule, peptide, protein engineering and targeted degradation, and translate it into an operating model, a methods roadmap and clear delivery standards for the unit /li liOwn ADMET/Safety as a strategic pillar in its own right: predictive safety and toxicology grounded in real experimental outcomes data, resourced and governed as a capability rather than as a sub-task of design /li liEnsure design decisions are informed by patient-derived multi-omics and disease context in close partnership with Computational Biology, so that chemistry starts from validated target biology, and act as decision authority for interface and prioritisation questions across the science units /li liDeliver the unit’s contribution to the named joint flagship programmes orchestrated by Strategy Portfolio, working to shared roadmaps with accountable delivery, schedule and quality /li liIndustrialise the capability by moving from project-by-project effort to repeatable, validated and benchmarked methods that scale across partner programmes,



with clear measures of predictive performance and impact on cycle time /li liBuild, develop and retain the team: hire and elevate senior scientific talent across sites, set technical and career development paths, and create the conditions for scientists to do their best work /li liEnable commercial value by supporting strategic partnership deals, model-training partnerships and asset licensing, and by evidencing in-silico attributed value together with Strategy Portfolio and Commercial /li liAct as a senior scientific and external voice for Evotec therapeutics design through partner and KOL engagement, publications and conferences, building recognition as a partner of choice in AI-powered drug discovery /li /ul h3Capability, Knowledge and Experience /h3 ul liDeep expertise in computational and/or medicinal chemistry, with hands-on command of structure-based and ligand-based design: docking, pharmacophore and QSAR modelling, molecular dynamics, and free energy methods such as FEP /li liWorking command of generative and predictive molecular design: generative models for molecule and sequence design, together with active learning and Bayesian optimisation applied to design-make-test-analyse cycles /li liDepth in at least one modality beyond small molecule (peptide, protein engineering, or targeted degraders), and the credibility to set technical direction across the others /li liStrong command of predictive ADMET, safety and toxicology modelling, including model validation, applicability domain, and the translation of predictions into project decisions /li liFamiliarity with protein structure prediction and modelling and its limitations (for example AlphaFold-class methods), and with protein-protein interface or ternary complex modelling for degraders and molecular glues /li liPractical understanding

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