About Iso
Isomorphic Labs (IsoLabs) was launched in 2021 to advance human health by building on and beyond the Nobel-winning AlphaFold system. Since then, our interdisciplinary team of drug discovery experts and machine learning specialists has built powerful new predictive and generative AI models that accelerate scientific discovery at digital speed.

Our name comes from the belief that there is an underlying symmetry between biology and information science. By harnessing AI’s powerful capabilities, we can use it to model complex biological phenomena to help design novel molecules, anticipate how drugs will perform and develop innovative medicines to treat and cure some of the world’s most devastating diseases.

Your impact
We’re looking for a data management specialist who is passionate about the curation and integration of high quality experimental data to support drug discovery projects. At IsoLabs you will be a core part of the data team, building our large scale, high quality data asset to power our next generation of groundbreaking AI/ML models.

What you will do

• Partner directly with discovery project teams to integrate experimental data generated throughout drug design cycles.
• Support drug design cycles so that all chemistry and biological assay data necessary to underpin project decision making is efficiently captured and available.
• Collaborate with internal and external teams to develop data exchange standards and implement user-friendly ELNs that ensure the integrity of ingested data.
• Apply your knowledge of chemical and/or biologics registration to facilitate effective compound management within internal databases.
• Contribute to the wider data team’s efforts to build a large, diverse, and high quality data asset that powers IsoLabs’ next generation of drug discovery ML models.
• Communicate your work and raise awareness of opportunities to improve data quality.

Skills and qualifications
Essential:

• Experience working in drug discovery informatics or data management roles for small and/or large molecule programs within the pharma/biotech industry.
• BSc, MSc or PhD degree in (bio)chemistry, pharmacology or relevant degree in the life sciences.
• Experience working with a broad range of experimental assay readouts used in the drug discovery process (e.g. in-vitro, biophysical and/or cellular assays; ADMET properties).
• Good knowledge of ontologies, data management systems and the curation of data to adhere to high standards of scientific quality.
• Experience using and configuring an Electronic Lab Notebook (ELN) system and defining robust data exchange standards with third parties.
• Working knowledge of Python and SQL with experience using cheminformatics and data science toolkits (e.g. RDKit, Pandas/Polars)
• Strong communicator and a proven collaborator with both multi-disciplinary biology/chemistry and product/engineering teams

Nice to have:

• Experience configuring and maintaining third-party drug discovery data management systems (e.g. Benchling, Dotmatics).
• Familiarity with data engineering concepts and experience with running jobs on Cloud-based infrastructure.

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).

We are committed to equal employment opportunities regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding) or any other basis protected by applicable law.