Hybrid In Vitro Pharmacology Leader

Isomorphic Labs

Cambridge

Hybrid

GBP 85,000 - 110,000

Full time

14 days+

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Benefits offered by this job

Hybrid work model

Job summary

Isomorphic Labs in Cambridge is seeking a Research Leader / Senior Scientist in Translational Sciences to lead in vitro pharmacology efforts within small molecule drug discovery. You will define screening cascades, guide assays, and collaborate with AI/ML, medicinal chemistry, and structural biology teams to advance targets toward clinical candidates.

The role includes line management for a 2–3 person team, mentoring and fostering a cross-disciplinary culture, and coordinating with CROs to

Qualifications

Ph.D. in Pharmacology, Biochemistry, Cell Biology, Biophysics, or a related scientific discipline.
8+ years / 5+ years of professional experience in a Translational Sciences role, in biotech, pharma or CRO.
Experience leading biology within small molecule drug discovery programs, from inception to clinical candidate delivery.
People management experience leading a high-performing scientific team.
Extensive experience designing and implementing biological screening cascades for drug design projects.
Deep knowledge of in vitro pharmacology techniques including biophysical, biochemical and/or cellular assays.
Ability to guide cross-functional programs and collaborate with CROs to deliver high-quality data.

Responsibilities

Design efficient and comprehensive biological screening cascades for internal and partnered drug design programs.
Guide the optimization and implementation of biophysical and biochemical assays (SPR, ITC, enzymatic) to evaluate binding, potency and specificity.
Direct the development of functional and phenotypic cellular assays to advance target validation and mechanistic understanding.
Collaborate with CROs to design decision-making experiments and deliver high-quality data for IND-enabling packages.
Interpret binding, kinetic and dose-response data; generate precise documentation to guide strategic decisions.
Bridge computational predictions with experimental data, coordinating with AI/ML, medicinal chemistry, structural biology, and translational sciences teams.