Team / Research Leader (Translational Oncology), London, Lausanne

Isomorphic Labs
Lausanne; LondonPosted 26 March 2026

Job Description

Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights, faster breakthroughs, and life-changing medicines with an ambition to solve all disease. The future is coming. A future enabled and enriched by the incredible power of machine learning. A future in which diseases are curtailed or cured starting with better and faster drug discovery. Come and be part of an interdisciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring and collaborative culture. The world we want tomorrow is the one we’re building today. It starts with the culture at this company. It starts with you. About Iso Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed. Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases. We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design. Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI. Your Impact We are seeking a Senior Translational Oncologist to serve as a key scientific leader to develop and execute the complete translational strategy for our diverse oncology pipeline, spanning multiple therapeutic modalities. You will work in a deeply collaborative, interdisciplinary partnership with our Computational Biology, AI/ML, Drug Design and Clinical teams. In this vital role, you will also be expected to line manage a team of Biologists, driving projects from discovery through to early clinical development. Your primary objective is to define the path to the clinic, and build the biomarker and patient selection strategies that ensure we get the right drug to the right patient, providing robust evidence that the target molecular profiles of AI-designed oncology drugs translate into desirable target product profiles. What you will do Translational Strategy: Design, lead, and execute comprehensive translational strategies for our oncology portfolio, establishing a clear line-of-sight from preclinical validation to clinical efficacy. Oncology Model Implementation: Ensure Isomorphic labs is choosing and accessing the most appropriate state-of-the-art in vivo and ex vivo cancer models (e.g. PDX, tumour organoids, syngeneic models, and complex co-cultures) to rigorously test mechanism of efficacy, resistance mechanisms, patient stratification, and dosing regimens. Biomarker PoC: Develop and implement robust biomarker and pharmacodynamic (PD) strategies, informed by in silico predictions, to secure early clinical proof-of-concept and guide patient selection in conjunction with Translational Medicine. AI/ML Partnership: Serve as the key oncology expert in a "computational-experimental" feedback loop. You will collaborate with Computational Biologists and ML Engineers to interpret in silico findings, design critical validation experiments, and integrate high-dimensional experimental data back into the AI platform to refine our models. Team Leadership Development: Lead a small team of drug discovery scientists who are responsible for ... (truncated, view full listing at source)
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