Research Scientist (Machine Learning, Cell and Tissue Biology), London

We are here to advance human health, by reimagining drug discovery with the power and pace of artificial intelligence. The future is coming. A future enabled and enriched by the incredible power of machine learning. A future in which diseases are curtailed or cured by better and faster drug discovery. Our values exist in service of that future. We think they’ll help us bring it closer, too. Come and be part of an interdisciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring and collaborative culture. The world we want tomorrow is the one we’re building today. It starts with the culture at this company. It starts with you.

About Iso

Isomorphic Labs (IsoLabs) was founded in 2021 and is led by Sir Demis Hassabis. Our aim is to usher in a new era of biomedical breakthroughs and find cures for some of humanity’s devastating diseases. Our foundations are built on the success of Google DeepMind’s AlphaFold, but we didn’t stop there! We are continuing to develop and implement state-of-the-art technologies as we move towards our goal of dramatically accelerating and improving the process of designing and bringing new medicines to patients. We have built a world-leading drug design engine comprising foundational AI models that are capable of working across multiple therapeutic areas and drug modalities. The company is continually innovating on model architecture and developing cutting-edge capabilities to advance rational drug design.

Your impact

This is an exciting opportunity for you to contribute to an ambitious Cell and Tissue Biology research program within the Computational Biology team, working in partnership with leading Machine Learning (ML) researchers, Chemists and Biologists. Building on the successful models in place to predict protein structure (AlphaFold-3), there is a unique opportunity for Research Scientists to have a direct impact on drug discovery using innovative ML approaches for modeling cells and tissues in health and disease. These are newly created roles; driven by a passion for problem solving, you will need to use your previous experience and show initiative in order to fully carve out your contribution.

What you will do

• Make original research contributions to enable machine learning model development, applied to cell and/or tissue biology, that impacts one or more critical problems in drug development.
• Identify and create novel ML approaches, model architecture, and training strategies, along with the required data to train.
• Analyse and tune experimental results to inform future experimental directions.
• Work within cross-functional ML Research, Chemistry, Engineering and Biology Teams, to direct research hypotheses and deliver outstanding research.
• Use your experience to undertake analysis of diverse computational biology datasets, including genetics, genomics, single-cell and bulk transcriptomics, proteomics, functional perturbation screens, imaging, knowledge graphs, PPI, clinical or other data types.
• Work in partnership with other Research & Development teams to evaluate the utility of research models, and incorporate feedback to ensure research outputs deliver high impact for drug design and development.
• Work with Bioinformatics, Data, and other groups to influence Iso’s datasets and pipelines strategy, to ensure innovative insights from these data are consistently brought to bear within drug development programmes.
• Perform thorough data analysis and data quality assurance checks, with a strong focus on accuracy and reproducibility, inline with industry standard processes.
• Work with other members of the Computational Biology team to deliver a unified team strategy.
• Report and present research findings and developments clearly and efficiently, and provide documentation, guidance, and communication on computational biology to the wider organisation.

Skills and qualifications

• Experience in computational biology specializing in cell and/or tissue biology, with PhD and research experience (i.e. postdoctoral or industry experience), or equivalent experience.
• Track record of delivery of outstanding research using deep learning techniques, including designing new ML architectures, hands-on experimentation, analysis, and visualisation.
• Strong knowledge of linear algebra, calculus, probability, and statistics.
• Demonstrated ability to write clean, idiomatic, and highly performant Python code.
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas.
• Expertise with detailed data quality control procedures and data visualisation.
• Experience with experimental design and statistical analysis.
• Demonstrated understanding of computational biology tools and methodologies and experience with the analysis of large -omics datasets.
• Familiarity with a variety of assaying techniques, including NGS, cell-based assays, functional genomics, single-cell techniques, and image-based assays and their respective data analysis approaches.
• Demonstrated understanding of the principles of molecular cell biology and genetics, or related biological disciplines.
• Familiarity with data processing pipelines and tools.
• Ability to effectively communicate scientific concepts to a variety of audiences.
• Experience in using Git for version control and familiarity with CI/CD concepts.
• Experience working in a Linux environment.
• Demonstrated ongoing career progression / trajectory and a passion for learning.

Nice to have:

• Experience in the context of therapeutic or diagnostic development programmes.
• Familiarity with structural biology and biochemistry.
• Experience working with complex data types, such as 3D epigenomics, long-reads, live imaging, and single-molecule localization microscopy.
• Familiarity with the current landscape of immuno-oncology research and therapeutic approaches.
• Experience working with clinical data.
• Experience in applying computational biology methods to the process of drug discovery, such as methods used for disease modelling and target discovery, combination strategies, as well as biomarker development.
• Experience applying computational biology workflows on Google Cloud Platform.

Culture and values

We are guided by our shared values. It's not about finding people who think and act in the same way. These values help to guide our work and will continue to strengthen it.

• Thoughtful: Thoughtful at Iso is about curiosity, creativity and care. It is about good people doing good, rigorous and future-making science every single day.
• Brave: Brave at Iso is about fearlessness, but it’s also about initiative and integrity. The scale of the challenge demands nothing less.
• Determined: Determined at Iso is the way we pursue our goal. It’s a confidence in our hypothesis, as well as the urgency and agility needed to deliver on it. Because disease won’t wait, so neither should we.
• Together: Together at Iso is about connection, collaboration across fields and catalytic relationships. It’s knowing that transformation is a group project, and remembering that what we’re doing will have a real impact on real people everywhere.

Creating an extraordinary company

We believe that to be successful we need a team with a range of skills and talents. We're building an environment where collaboration is fundamental, learning is shared and every employee feels supported and able to thrive. We value unique experiences, knowledge, backgrounds, and perspectives, and harness these qualities to create extraordinary impact. 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.

If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. 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.