Research Leader - In-vitro Pharmacology, Exploratory Sciences

About the Exploratory Sciences Team

You will be joining the expanding “Exploratory Sciences” team, focused on tackling proteins which are critical for disease biology, but have been traditionally considered intractable. 

We are a  multidisciplinary team within the Drug Design and Medical Research function at Isomorphic Labs. We work where machine learning, chemical biology and drug discovery meet, applying the Isomorphic Labs platform to some of the hardest problems in the field.

Our work goes beyond individual targets. We explore emerging therapeutic modalities,  molecular glues and peptides to modalities that don't have a playbook yet. We also design the data generation strategies that make these modalities workable for AI-driven design. The experiments we run don't just move drug-discovery  programmes forward - They shape the models that power Iso's drug design engine.

We're as comfortable in silico as we are at the bench. Our scientists build and test hypotheses computationally, use LLM-based agentic workflows in their daily science, and work alongside ML researchers and engineers on Platform builds. We work closely with teams across Isomorphic Labs, so ideas move quickly from model to real world experiments and back again, keeping the goal of  drug discovery and development front and centre .

Above all, we're curious and ambitious, and we care about growth. We put continuous learning and development first, because we're building the next generation of drug discovery scientists. If you want to help define what drug discovery looks like next, you'll fit right in.

Your impact 

We're looking for an accomplished in vitro pharmacology leader to build and lead a team of biologists in Exploratory Sciences, and to shape how Iso tests and validates new therapeutic modalities.

You'll own the experimental pharmacology strategy across our exploratory portfolio. You'll decide which questions are worth asking, which assays and cascades will answer them, and what "decision-quality" means for modalities that don't have an established playbook yet. Your judgement will directly shape which ideas move forward.

You'll make the data count twice. Every experiment your team designs should move a programme forward and also make our models smarter. You'll work out if  the platform has a blind-spot, then innovate on assays to generate the datasets that fill it. The result is a closer loop between in silico predictions and experimental results.

You'll set the standard for how modern biologists work. You'll lead by example in using LLM agentic workflows and in silico hypothesis building, and help your team make them a natural part of daily science. Working as an equal partner with ML, engineering and computational colleagues, you'll help shape the tools your team relies on.

You'll mentor a team of research investigators who are experienced  bench scientists and fluent in applying creative ai-first approaches to drug discovery , and help them become the leaders Exploratory Sciences needs as it continues to  expand..

Ready to elevate your scientific career? Isomorphic Labs offers ambitious scientists a unique environment to tackle stimulating challenges, pushing your boundaries and accelerating your personal and professional growth. If you are a skilled and ambitious scientific leader  looking to take the next step in your career, Isomorphic Labs will provide you with that amazing opportunity unlike any other.

What you will do: 

Modality Strategy & Target Prosecution:

• Set the in vitro pharmacology vision for exploratory programmes across TPD, molecular glues, peptides and next-generation modalities.
• Assess the tractability of new modalities against challenging targets and set rigorous go/no-go criteria.

Screening Cascades & Mechanistic Pharmacology:

• Turn therapeutic concepts and TPPs into rigorous screening cascades for internal and partnered programmes.
• Lead the design of biochemical, biophysical (e.g. SPR/GCI, nanoDSF, Spectral Shift, MST) and bespoke screening cascades for novel modalities.
• Develop quantitative assays covering binding kinetics, ternary complexes, degradation and functional pathway readouts (e.g. HiBiT, NanoBRET, TR-FRET).
• Work closely with medicinal chemistry and DMPK to drive SAR and compound de-risking.
• Set data quality, ontology and QC standards so that internal and CRO data are ML-ready from the start.

AI, Agentic Workflows & Platform Builds:

• Champion the use and co-development of LLM agentic workflows to speed up hypothesis generation, experimental design and data synthesis.
• Work with ML and engineering teams on Platform builds, contributing biological domain expertise to model and workflow design.
• Test in silico hypotheses rigorously in the wet lab and build plans that move programmes forward and fill systematic gaps in our models.
• Give stakeholders and collaborative teams critical biological input to guide generative design for new modalities.

Scientific Leadership & External Partnerships:

• Lead a team of Research and Senior Research Investigators, with roughly a 50:50 split between scientific direction and people and CRO leadership.
• Design, manage and lead execution on  CRO and academic studies that deliver decision-quality data.
  
  

Skills and qualifications 

Essential:

• PhD or equivalent industrial/research experience in Pharmacology, Biochemistry, Biophysics, Cell Biology or a related discipline, with significant years in biotech or pharma drug discovery.
• Expert knowledge of in vitro pharmacology and biophysics, including designing robust screening cascades from Target ID through Hit-to-Lead and Lead Optimisation.
• Hands-on experience with one or more novel modalities (e.g. TPD, molecular glues, peptides, induced proximity).
• Proven experience leading and developing scientists and managing CRO studies.
• Experience with, or clear enthusiasm for, LLM agentic workflows, in silico hypothesis building and data-driven discovery.
• Highly collaborative, agile, and motivated by a fast-moving, interdisciplinary environment with ability to work across many projects and therapeutic areas
• Effective communication across a broad interdisciplinary team, working with key stakeholders with different skills and backgrounds

Nice to have:

• Experience validating virtual screens, de novo designs or ML-predicted binders.
• Experience with lab automation and high-throughput data infrastructure.
• Scripting or data analysis skills (e.g. Python, R) or experience building agents or prompts for scientific workflows.
• Track record of authorship of relevant scientific manuscripts, patents etc