Applied Machine Learning Researcher

Company Description

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.

Job Description

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, preferred. 
• Record of publications in peer-reviewed journals and conferences closely related to the above. 

Additional Information

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 application.

Being an integral part of such a meaningful mission is extremely rewarding in itself, but in order to support our people, we’re continually improving our benefits package. We pride ourselves on investing in our people and supporting them to achieve their career goals, as well as offering a benefits package including: 

• Generous Leave: 30 days’ holiday plus bank holidays, additional leave for long service, and the option to apply for up to 30 days of remote working abroad annually (approval required).
• Family-Friendly: Blended working arrangements, flexible working, enhanced maternity, paternity and shared parental leave benefits.
• Pension & Financial: Defined contribution pension (Genomics England double-matches up to 10%, however you can contribute more if you wish), Life Assurance (3x salary), and a Give As You Earn scheme.
• Learning & Development: Individual learning budgets, support for training and certifications, and reimbursement for one annual professional subscription (approval required).
• Recognition & Rewards: Employee recognition programme and referral scheme.
• Health & Wellbeing: Subsidised gym membership, a free Headspace account, and access to an Employee Assistance Programme, eye tests, flu jabs.

Equal opportunities and our commitment to a diverse and inclusive workplace 

Genomics England is actively committed to providing and supporting an inclusive environment that promotes equity, diversity and inclusion best practice both within our community and in any other area where we have influence. We are proud of our diverse community where everyone can come to work and feel welcomed and treated with respect regardless of any disability, ethnicity, gender, gender identity, religion, sexual orientation, or social background. 

Genomics England’s policies of non-discrimination and equity and will be applied fairly to all people, regardless of age, disability, gender identity or reassignment, marital or civil partnership status, being pregnant or recently becoming a parent, race, religion or beliefs, sex or sexual orientation, length of service, whether full or part-time or employed under a permanent or a fixed-term contract or any other relevant factor.  

Genomics England does not tolerate any form of discrimination, harassment, victimisation or bullying at work. Such behaviour is contrary to our virtues, undermines our mission and core values and diminishes the dignity, respect and integrity of all parties.  Our People policies outline our commitment to inclusivity. 

We aim to remove barriers in our recruitment processes and to be flexible with our interview processes. Should you require any adjustments that may help you to fully participate in the recruitment process, we encourage you to discuss this with us. 

Blended working model

Genomics England operates a blended working model as we know our people appreciate the flexibility that hybrid working can bring. We expect most people to come into the office a minimum of 2 times each month. However, this will vary according to role and will be agreed with your team leader. There is no expectation that people will return to the office full time unless they want to, however, some of our roles require full time on site attendance e.g., lab teams, reception team. 

Our teams and squads have, and will continue to reflect on what works best for them to work together successfully and have the freedom to design working patterns to suit, beyond the minimum. Our office locations are: Canary Wharf, Cambridge and Leeds.

Onboarding background checks

As part of our recruitment process, all successful candidates are subject to a Standard Disclosure and Barring Service (DBS) check.  We therefore require applicants to disclose any previous offences at point of application, as some unspent convictions may mean we are unable to proceed with your application due to the nature of our work in healthcare.