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Isomorphic Labs

AI-powered drug discovery and development

Senior Research Investigator / Research Leader - Translational Pharmacology

Translational Research & Bench BiologyConfirmed live in the last 24 hours
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • A 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 Contract Research Organisations and academic collaborators.
  • Experience collaborating closely with bioinformatics, cheminformatics, or computational biology teams, utilising data-driven approaches for target discovery and compound progression.

Responsibilities

  • Partner with therapeutic area leadership to define and evolve the 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.
  • Develop human disease-relevant therapeutic hypotheses that connect target modulation directly to clinically meaningful outcomes.
  • Translate therapeutic concepts and target product profiles into biologically rigorous screening cascades for internal and partnered programs.
  • Profile novel chemical matter emerging from 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.
  • 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 machine learning teams to guide and inform generative models of biological systems and disease pathways.
  • 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 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.

Desired Qualifications

  • Track record of driving strategic compound de-risking and structure–activity relationship work in close collaboration with medicinal chemistry and DMPK teams.
  • Working knowledge of biophysical, biochemical, and cellular screening techniques, including surface plasmon resonance, TR-FRET, mass spectrometry, and 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.

About the Company

Isomorphic Labs

AI-powered drug discovery and development

Isomorphic Labs uses artificial intelligence to speed up drug discovery and development. It applies machine learning and computational methods—building predictive and generative models—to accelerate how drugs are designed and how medical research is conducted. The company differentiates itself by combining the AI breakthroughs from Google DeepMind with Alphabet backing, enabling fast experimentation and scaling across biology while maintaining startup-style agility. Its goal is to bring safer, more effective therapies to market more quickly by advancing AI-driven medicine using deep learning, reinforcement learning, and other advanced techniques.

Company size
201-500
Company stage
Series C
Total funding
$7.7B
Headquarters
London, United Kingdom
Founded
2021

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