Research Scientist - Statistical Genetics (Computational Biology), London

Research Scientist - Statistical Genetics (Computational Biology) London

Isomorphic Labs is applying frontier AI to help unlock deeper scientific insights faster breakthroughs and life-changing medicines with an ambition to solve all disease.

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 starting with better and faster drug discovery.

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 were building today. It starts with the culture at this company. It starts with you.

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 AIs 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 worlds 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 were 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 for you to join the Computational Biology team and to help build AI first approaches to understanding causal human biology. The role provides a clear line-of-sight from research to capability build through to impact on our drug development programs and ultimately to patients lives. Collaborating with Machine Learning Bioinformatics Data Product and Drug Discovery teams you will use your experience in statistical genetics to provide scalable and innovative analysis of human genetic data. The new understanding of human biology that your work will generate will integrate with the broader research program in Computational Biology to provide actionable insights for drug development.

What you will do

• Use your experience to undertake analysis of human genetics and genomics datasets in combination with high-dimensional molecular measurement clinical and phenotypic data and models of biological systems to infer causal biology.
• Explore and assess approaches to analysis by implementing algorithms that can be applied at scale taking advantage of available computational cross-functional and data resources.
• 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 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 Isos 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 statistical genetics and genomics 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 statistical genetic 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 concepts in the training testing and deployment of machine learning algorithms
• Familiarity with data processing pipelines and tools
• Ability to effectively communicate scientific concepts to a variety of audiences
• Strong Python software development and analysis skills with experience in modern software practices (CICD version control testing code review)
• Experience using common database platforms and data integration approaches
• Experience working in a Linux environment and performing analysis in a cloud environment (ideally GCP)
• 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 complex phenotype data (medical records high-dimensional phenotypes).
• Experience in working within a research analysis platform (for example the UK Biobank RAP AllofUs Workbench).
• Previous training in dealing with sensitive data (GDPR PII PHI etc) and track record of good data governance.
• 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 algorithmic software in Python
• Experience in working with containers: docker Kubernetes or similar.

Culture and values

We are guided by our shared values. Its 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 its also about initiative and integrity. The scale of the challenge demands nothing less.

Determined
Determined at Iso is the way we pursue our goal. Its a confidence in our hypothesis as well as the urgency and agility needed to deliver on it. Because disease wont wait so neither should we.

Together
Together at Iso is about connection collaboration across fields and catalytic relationships. Its knowing that transformation is a group project and remembering that what were 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. Were 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.

Hybrid working

Its 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 youre in). If you have additional needs that would prevent you from following this hybrid approach wed be happy to talk through these if youre selected for an initial screening call.

Please note that when you submit an application your data will be processed in line with our .

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