Your impact

Isomorphic Labs are seeking exceptional individuals to join a highly impactful In vitro and Cellular Pharmacology sub-team, within our Translational Sciences team. This role is ideal for an experienced in vitro pharmacologist with significant working knowledge of biophysical, biochemical and/or cell-based functional assays, and extensive experience of providing quantitative in vitro pharmacology expertise within drug discovery projects.

This is an exciting opportunity to work closely with world-leading ML and drug discovery experts to develop imaginative new ways to test biological hypotheses, building a deep mechanistic understanding of drug target interactions to drive our projects forward. You will play a key role in defining the screening cascades for our drug design projects, advancing our oncology, immunology and partnership portfolios from early drug discovery through to candidate selection and ultimately to clinical phase work. By overseeing externalized CRO activities, you will close the loop between computational biological insights and real-world laboratory validation. You will have experience of working broadly across drug discovery projects and have the ability to think originally and critically, knowing when to apply innovative ideas, and think with a fresh approach.

What you will do

• Design efficient and comprehensive biological screening cascades for a variety of internal and partnered drug design programs.
• Guide the optimization and implementation of biophysical and biochemical assays, including SPR, ITC, and enzymatic methodologies, to rigorously evaluate target interaction, pharmacological potency, and molecular specificity.
• Direct the development and refinement of functional and phenotypic cellular assays, bridging the gap between biochemical engagement and biological potency to advance target validation and mechanistic understanding.
• Work with CROs to design decision-making experiments, and deliver the highest quality biological data to inform the path to the clinic.
• Evaluate, interpret, and synthesize complex binding, kinetic, and dose-response information; generate precise technical documentation to guide strategic decision-making and support IND-enabling data packages.
• Act as a vital bridge between computational prediction and experimental reality, collaborating closely with:
• AI/ML and Data Science teams: To translate in silico predictions into testable hypotheses and provide clean data loops to train future models.
• Medicinal Chemistry: To guide SAR-driven design cycles with rapid, reliable potency and selectivity data.
• Structural Biology: To align biophysical binding data with structural insights informing lead optimization.
• In vivo Pharmacology and Translational Sciences: To ensure a seamless handoff of validated leads into in vivo efficacy and translational study design.

Skills and qualifications
Essential:

• Ph.D. in Pharmacology, Biochemistry, Cell Biology, Biophysics, or a related scientific discipline.
• Extensive experience in the design and implementation of biological screening cascades applied to drug design projects from hit identification to candidate selection phases.
• Deep knowledge of experimental in vitro pharmacology techniques including biophysical, biochemical and/or cellular assays.
• Ability to provide technical guidance within matrixed organizations, effectively steering cross-functional programs and execution through collaboration.
• Experience working with CROs in acquiring and interpreting high quality biological data in a timely manner.
• Dynamism and agility, with ability to work across several projects and therapeutic areas.
• Effective communication across a broad interdisciplinary team, working with key stakeholders with different skills and backgrounds.

Nice to have:

• Experience of leading biology within drug discovery programs, ideally from inception to clinical candidate delivery.
• Experience partnering with Data Science groups in setting up systems for ingestion of biological data.
• Track record of contributing to drug design projects which have then delivered Clinical Candidates.
• Working knowledge of designing and implementing assays and screening cascades for alternative modalities or alternative chemistries e.g peptides or molecular glues.
• General knowledge of machine learning modelling applied to biological systems and drug discovery.

Hybrid working

It's hugely important for us to share knowledge and build strong relationships with each other, and we find it easier to do this if we spend time together in person. This is why we follow a hybrid model, and would require you to be able to come into the office 3 days a week (currently Tuesday, Wednesday, and one other day depending on which team you're in). If you have additional needs that would prevent you from following this hybrid approach, we'd be happy to talk through these if you're selected for an initial screening call.

Please note that when you submit an application, your data will be processed in line with our privacy policy.

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