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Isomorphic Labs

AI-powered drug discovery and development

Research Leader / Senior Research Investigator - Translational Biology & In-Vitro Pharmacology

Translational Research & Bench BiologyPosted on Nov 13
Full-timeLondon, UKNo salary listed

About the Job

Requirements

  • A BSc, MSc, or PhD in Pharmacology, Cellular/Molecular Biology, Physiology, Neuroscience, or a relevant field of biology is required.
  • Extensive hands-on and strategic pharmaceutical or biotech experience designing and implementing biological screening cascades for drug design projects across Hit Identification, Hit-to-Lead, Lead Optimisation, and Candidate Selection phases is required.
  • Deep knowledge of experimental in-vitro pharmacology techniques, including biophysical, biochemical, and cellular functional assays such as ELISA, HTRF, FP, Cellular Proliferation/Health, nanoBRET, High Content Screening, Reporter Gene, and primary human cell assays, is required, with the ability to select and interpret suitable assays for diverse target classes and biological contexts.
  • A profound understanding of target, mechanism, and disease interdependencies, together with expert knowledge of innovative translational models relevant to maximised Healthspan, such as musculoskeletal and regenerative health or pulmonary and systemic disease, is required.
  • Experience in project leadership or leading biology within drug discovery programs, with a track record of contributing to projects from inception through Clinical Candidate delivery, is required.
  • Extensive experience developing Target Product Profiles (TPPs) and translating them into lean, impactful biological screening cascades to guide drug development toward clinically meaningful medicines is required.
  • A proven track record constructing comprehensive translational data packages, target liability assessments, and clinical biomarker strategies—including target engagement, pharmacodynamic, and patient stratification biomarkers—to inform clinical trial design is required.
  • Experience designing PK/PD experiments to establish quantitative exposure-target engagement-efficacy relationships for human dose prediction is required, collaborating closely with ADMET, formulation, and clinical pharmacology specialists to refine preclinical and clinical strategies.
  • The ability to collaboratively phase in-vitro pharmacology and translational biology activities, proactively considering interdependencies to efficiently generate decision-quality data, is required.
  • Demonstrated experience working with CROs to acquire, quality-control, and interpret high-quality biological data in a timely manner is required.
  • Demonstrated ability to work successfully with co-development partners to progress drug discovery programs within teams comprising internal and external stakeholders is required.
  • Ability to navigate numerous projects, diverse therapeutic areas, and multidisciplinary teams with a focused approach to Candidate delivery is required.
  • Communication skills to foster effective collaboration and shared learning across interdisciplinary teams and with stakeholders from diverse backgrounds are required.

Responsibilities

  • Design and implement efficient, fit-for-purpose biological screening cascades for internal and partnered drug design programs from Hit Identification through Candidate Selection, focusing on translating quantitative in-vitro pharmacology and preclinical studies into clinical efficacy within target patient populations.
  • Provide technical and strategic expertise across biochemical, biophysical, and cellular functional assays for diverse protein targets to characterize compound mechanism of action, potency, selectivity, and structure-activity relationships.
  • Define appropriate translational model paradigms, including in vivo disease models, ex-vivo patient-derived tissue, iPSC-derived systems, and complex 3D organoids, for project translational packages in the Healthspan therapeutic area, and develop biomarker strategies to secure early clinical proof of concept.
  • Collaborate with Contract Research Organizations and external partners to design decision-making experiments and oversee assay development, validation, and troubleshooting to deliver high-quality biological data.
  • Work with the business development team to scientifically assess collaborative opportunities to co-develop medicines to maximise healthspan.
  • Work with external drug discovery teams to progress programs.
  • Provide scientific expertise to AI/ML and computational biology teams through a bidirectional experimental-computational feedback loop, supporting development and refinement of models of biological systems.
  • Distill complex pharmacological and translational biological data into actionable insights and strategic recommendations for project leaders, team members, ML researchers, and external partners.
  • Be integrated within or lead multidisciplinary drug discovery projects, providing strategic biological input from early discovery through clinical candidate nomination.
  • Contribute to internal candidate nomination packages and supporting regulatory documentation, including IND/CTA filings, for preclinical and clinical work.
  • Collaborate closely with Drug Design, Medicinal Chemistry, DMPK/ADMET, and Technology teams.

Desired Qualifications

  • Demonstrated experience leveraging Large Language Models and generative AI tools to enhance scientific workflows, such as literature and target-landscape synthesis, experimental protocol and screening cascade design, pharmacological or biomarker data extraction, or hypothesis generation.
  • A track record of driving strategic de-risking, anticipating longer-term translational hurdles, and influencing medicinal chemistry SAR strategies, supported by an understanding of small molecule medicinal chemistry and DMPK concepts.
  • Working knowledge of designing and implementing assays and translational screening cascades for alternative modalities or novel chemistries, such as peptides, molecular glues, targeted protein degraders, ADCs, or oligonucleotides.
  • Experience partnering with Computational Biology and Data Science groups to configure systems for biological/pharmacological data ingestion and apply machine learning modeling concepts to biological systems and drug discovery.
  • Practical experience in early target identification, causal genetic/functional validation, and indication selection across multiple biological mechanisms and routes of administration.
  • Expertise or working familiarity with protein expression/purification techniques and compound management workflows to support early assay setup and hit triage.
  • Experience working with business development to assess potential scientific or strategic opportunities in drug discovery.

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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