Research Scientist (Computational Biology, Cells and Tissues), London

Research Scientist (Computational Biology, Cells and Tissues), London

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 an 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

Essential:

• 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

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.