Your impact

We are seeking an accomplished and visionary translational biologist to join our Translational Pharmacology team in London, working at the forefront of multidisciplinary, AI-first drug discovery.

In this role, you will shape and advance our exploratory research portfolio, with an initial core focus on neurodegenerative diseases as well as adjacent high unmet need indications. Operating at the interface of disease biology, translational science, and AI-driven molecular design, you will translate deep mechanistic insights of human disease into robust therapeutic hypotheses, target validation packages, and decision-critical experimental workflows to progress programs from target identification to portfolio entry. Working shoulder-to-shoulder with world-leading machine learning researchers, computational biologists, and drug designers, you will bridge the gap between dry-lab predictive models and experimental biology—ensuring our AI platforms are grounded in disease-relevant biology and guiding next-generation medicines towards clinical reality.

What you will do

Therapeutic Area Strategy & Target Discovery:

• Partner with therapeutic area leadership to define and evolve our neurodegeneration research strategy, identifying priority indications, emerging biological mechanisms, and high-value therapeutic opportunities.
• Integrate insights across human genetics, disease pathology, clinical datasets, and advanced cellular models to critically evaluate target tractability, translational relevance, and competitive differentiation.
• Drive early portfolio progression decisions by establishing rigorous go/no-go target validation criteria.

Translational Biology & Experimental Execution:

• Develop human disease-relevant therapeutic hypotheses that connect target modulation directly to clinically meaningful outcomes.
• Translate therapeutic concepts and target product profiles (TPPs) into biologically rigorous screening cascades for internal and partnered programs.
• Profile novel chemical matter emerging from our in silico generative design pipelines, building comprehensive pre-clinical data packages.
• Embed early translational thinking around target engagement indicators, translational biomarkers, and patient stratification strategies.

Cross-Functional Collaboration with AI/ML Teams:

• Work closely with AI/ML, computational biology, and structural biology teams to design assays and experimental systems that meaningfully benchmark and evaluate AI-designed molecules.
• Provide critical biological domain expertise to ML teams to guide and inform generative models of biological systems and disease pathways.

Scientific Leadership & External Partnerships:

• Serve as the scientific lead for portfolio programs, directing scientific strategy, managing timelines, and ensuring the delivery of decision-quality data.
• Design, oversee, and manage outsourced studies with external Contract Research Organisations (CROs) and academic/co-development collaborators.
• Maintain strong awareness of global scientific advances, competitive clinical landscapes, and emerging translational technologies in neurodegeneration and diseases of aging.

Skills and qualifications

Essential:

• PhD or equivalent industrial/research experience in Neuroscience, Translational Medicine, Pharmacology, Cellular/Molecular Biology, or a related discipline.
• Deep mechanistic understanding of neurodegenerative disease biology, including cellular and molecular drivers of pathology in complex, high-unmet-need indications.
• Expert practical knowledge of translational models (in vitro, ex vivo, and in vivo), patient-derived cellular systems, and the design of robust screening cascades from Target ID through Hit-to-Lead/Lead Optimisation.
• Demonstrated success in advancing therapeutic hypotheses through target validation and profiling novel chemical matter to build decision-quality data packages.
• Proven experience designing, contracting, and managing external research studies with CROs and academic collaborators.
• Experience collaborating closely with bioinformatics, cheminformatics, or computational biology teams, utilising data-driven approaches for target discovery and compound progression.
• Highly collaborative, agile, and driven to thrive in a high-velocity, interdisciplinary team environment.

Nice to have:

• Track record of driving strategic compound de-risking and SAR in close collaboration with medicinal chemistry and DMPK teams.
• Working knowledge of biophysical, biochemical, and cellular screening techniques (e.g., SPR, TR-FRET, mass spectrometry, high-content imaging) and how machine learning models interact with these assay outputs.
• Broad biological experience in diseases of aging or neuroinflammation outside classical neurodegeneration.
• Prior experience in early clinical biomarker discovery or target engagement assay development.