Research Scientist - Statistical Genetics (Computational Biology), London
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 we’re 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 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 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 patient’s 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 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
- 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. 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, andwould 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.
Please note that when you submit an application, your data will be processed in line with our privacy policy .
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