Data Curator

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.

We have built a world-leading drug design engine comprising AI models that are capable of working across multiple therapeutic areas and drug modalities. We are continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design.

Every day, and with each new breakthrough, we’re getting closer to the promise of digital biology, and achieving our ambitious mission to one day solve all disease with the help of AI.

Your impact

This is an exciting opportunity to join the data team at IsoLabs, working closely with world leading AI experts and Drug Discovery scientists to establish machine learning ready datasets that power the discovery of the next generation of medicines. As a data curator you will be foundational in ensuring the quality of data at scale and lead our efforts to represent chemical, biological, and clinical information in the most impactful way for IsoLabs, an AI driven drug-discovery platform.

What you will do

• Integrate large scale biomedical and biochemical datasets and curate them to enhance their quality and create interoperable data assets that fuel IsoLabs research efforts.
• Work in partnership across research teams to create ML-ready datasets.
• Use your expertise in chemistry and/or biology to maximise the quality and scale of available training data.
• Contribute to the data team’s efforts to identify, evaluate and assess new data sources and data generation opportunities.
• Collaborate to devise novel ways to couple machine learning based data extraction methods with human domain expertise to build large scale high-quality datasets.
• Communicate your work and raise awareness of opportunities to improve data quality.

Skills and qualifications

Essential:

• Proven experience working in industry at a biotech or pharmaceutical company or closely with industry at a research institution.
• PhD in a Life Science or Informatics discipline, or equivalent experience in scientific research.
• Expert in data representation, ontologies, and curation of high quality data assets.
• Experience working with a broad range of data types used in the drug discovery process (e.g. binding assays, ADMET properties).
• Deep knowledge of biomedical and biochemical databases and data sources and approaches to improve their interoperability for machine learning use cases.
• 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:

• Familiarity with data engineering concepts and experience with running jobs on Cloud-based infrastructure.