Research Scientist (Computational Biology), Lausanne

Research Scientist (Computational Biology), London

Isomorphic Labs is a new Alphabet company that is reimagining drug discovery through a computational- and AI-first approach.

We are on a mission to accelerate the speed, increase the efficacy and lower the cost of drug discovery. You'll be working at the cutting edge of the new era of 'digital biology' to deliver a transformative social impact for the benefit of millions of people.

Come and be part of a multi-disciplinary team driving groundbreaking innovation and play a meaningful role in contributing towards us achieving our ambitious goals, while being a part of an inspiring, collaborative and entrepreneurial culture.

Your impact

This is an exciting opportunity for you to contribute to an ambitious Computational Biology research programme, 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 Computational Biology and ML approaches. 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 computational biology, that impacts one or more critical problems in drug development.
• 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 computational biology datasets, including genetics, genomics, 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.
• Provide documentation, guidance, and communication on computational biology to the wider organisation.

Skills and qualifications

Essential:

• Experience in computational biology, with PhD and research experience (i.e. postdoctoral or industry experience), or equivalent experience
• Track record of delivery of outstanding research
• 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
• 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
• Programming skills in a language such as Python (ideally), or R
• Experience using common database platforms, and data integration approaches
• Experience working in a Linux environment
• Demonstrate ongoing career progression / trajectory and a passion for learning

Nice to have:

• Prior experience in the context of therapeutic or diagnostic development programmes
• Familiarity with a variety of assaying techniques, including NGS, cell-based assays, functional genomics, single-cell techniques, and image-based assays with expertise in their respective data analysis approaches
• Experience working with clinical data
• Expertise 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
• Experience in developing software in Python
• Hands-on experience in applying ML (especially deep learning) models in the field of computational biology.