Applied Machine Learning Researcher (we have office locations in Cambridge, Leeds & London)

Genomics England; London; On-site; GBP 70,000 - 82,000; Full time

Job summary

A leading company in genomic healthcare is seeking an Applied Machine Learning Researcher to join their London office. The successful candidate will focus on multi-omics data analysis, driving innovation in bioinformatics and contributing to scientific publications. This role offers the opportunity to work with unique datasets and collaborate with cross-functional teams to enhance genomic research capabilities.

Qualifications

• Experience in applying ML to omics data.
• Record of publications in peer-reviewed journals.
• Experience with multi-omics data integration.

Responsibilities

• Conduct research using multi-omics data.
• Develop ML approaches for biological datasets.
• Collaborate with teams to advance research initiatives.

Skills

Bioinformatics

Computational Biology

Machine Learning

Data Privacy

Statistical Methods

Python

Communication

Education

PhD in Bioinformatics

MSc in Computational Biology

Tools

AI Development Frameworks

Cloud-native Development

Job description

Applied Machine Learning Researcher (we have office locations in Cambridge, Leeds & London)

• Full-time
• Office: London

Genomics England partners with the NHS to provide whole genome sequencing diagnostics. We also equip researchers to find the causes of disease and develop new treatments – with patients and participants at the heart of it all.

Our mission is to continue refining, scaling, and evolving our ability to enable others to deliver genomic healthcare and conduct genomic research.

We are accelerating our impact and working with patients, doctors, scientists, government, and industry to improve genomic testing, and help researchers access the health data and technology they need to make new medical discoveries and create more effective, targeted medicines for everybody.

We are seeking a researcher specialising in multi-omics data analysis and ML applications to join our team. The successful candidate will contribute to research initiatives using our unique datasets (particularly those in the National Genomic Research Library, NGRL), and drive innovation in the integration of multi-omics data sources. This role combines cutting-edge research with practical applications in bioinformatics, biomedical data science, or related clinically-oriented areas. You will collaborate with internal teams and external partners to develop novel applications for analysing complex biological data, particularly in areas such as transcriptomics, proteomics, and metabolomics. This position offers the opportunity to contribute to scientific publications while developing AI tooling that advances our research capabilities and ensures responsible use of our participant data.

Everyday responsibilities include:

• Design and conduct research using our datasets, with a focus on multi-omics data integration techniques and applications.
• Develop and implement ML approaches to extract meaningful insights from complex biological datasets to enable research in rare conditions and cancers. This includes different phases of the ML development cycle, including data pre-processing and rigorous model evaluation.
• Collaborate with cross-functional teams and external partners to advance research initiatives.
• Evaluate and adopt AI tooling to enhance our research capabilities, with emphasis on decision support tools for ensuring data privacy and preventing data leakage from ML models.
• Contribute to peer-reviewed publications and present research findings at scientific conferences.
• Act as a go-to person by providing expertise on AI-enabled multi-omics data analysis to support broader company research-focused objectives.

Skills and experience for success:

• Research experience in Bioinformatics, Computational Biology, or related field based on the application of ML approaches.
• Proven experience applying ML techniques to at least one type of omics data (transcriptomics, proteomics, metabolomics, or spatial omics).
• Experience with multi-omics data integration and analysis, e.g., using graph models, with preference for spatial omics expertise.
• Author of publications in peer-reviewed journals and presentations at top conferences relevant to the role.
• Proficiency in Python, major AI development frameworks, and cloud-native development.
• Strong understanding of statistical methods for enabling high-quality research.
• Ability to work collaboratively in cross-functional teams and with external academic partners.
• Strong written and verbal communication skills for research dissemination.
• Self-directed and learning seeking, with passion for problem-solving and attention to detail.
• Experience evaluating ML model risks, particularly for addressing data privacy concerns in research settings, is considered an advantage.

Qualifications:

• PhD or MSc in Bioinformatics, Computational Biology, Applied ML, or closely related field.
• Practical experience with at least one type of omics data analysis using AI is essential. Multi-omics integration, e.g., spatial omics data models, is preferred.
• Record of publications in peer-reviewed journals and conferences closely related to the above.

Salary from £70,500

Please submit your CV and cover letter (1 page) outlining how your skills and experience align with the role. Additionally, we kindly ask you to select and reference an article you have authored in a peer-reviewed journal in (PDF) format or other recognised publication. Please note without this we are unable to progress your application.