Senior Research Associate - Multimodal Machine Learning for Breast Cancer Research (Fixed Term)

University of Cambridge; Cambridge; On-site; GBP 35,000 - 45,000; Full time

Job summary

The University of Cambridge is seeking an ambitious machine learning scientist for the Precision Breast Cancer Institute. The successful candidate will develop innovative algorithms for multimodal data analysis to enhance breast cancer treatments and outcomes. Join a collaborative team dedicated to impactful research and advancements in patient care.

Qualifications

• Experienced machine learning scientist with a strong background in multimodal data analysis.
• Prior experience in clinical research and algorithm development is essential.
• Ability to work collaboratively in a multidisciplinary team.

Responsibilities

• Design and develop new machine learning algorithms to analyze large-scale cancer data.
• Collaborate with clinical experts and contribute to high-impact research publications.
• Mentor PhD students and Research Associates in computational projects.

Skills

Machine Learning

Data Analysis

Multimodal Data Interpretation

Education

PhD in a relevant field

Job description

This is an exciting opportunity for an experienced, ambitious, talented, and highly motivated machine learning scientist to join our team within the Precision Breast Cancer Institute https://crukcambridgecentre.org.uk/research/programmes/breast-cancer/pbci (PBCI), led by Professor Jean Abraham, and make a real impact in the fight against breast cancer.

Breast cancers comprise complex biological processes that function in compound microenvironments of malignant tumour cells. As such, incorporating and simultaneously analysing multimodal data can offer a better understanding of the underlying cancer mechanisms, ultimately leading to more accurate diagnosis, prognosis, and treatment planning for cancer patients. Breast cancer research produces complex multimodal data at different scales, including clinical, imaging (radiology and digital pathology), and genomic or transcriptomic profiles. The successful candidate will play a pivotal role in revolutionising patient care through the design, development, and application of novel machine learning methods to analyse and interpret large-scale multimodal data using samples primarily derived from large clinical trials and studies. The role will also involve working closely with renowned scientists, liaising with project teams and external science users, contributing to research publications, and collaborating with clinical experts to optimise the interpretation and use of these data.

At PBCI, we believe in fostering a collaborative and supportive work environment. We value teamwork, respect, and open communication, creating a space where ideas thrive and individuals flourish. Together, we will support and inspire one another as we work towards our shared goal of improving breast cancer treatments and outcomes. Together, we will shape the future of breast cancer research and drive impactful and rapid change.

The successful candidate will line manage, support, and develop Research Associates and PhD Students, as well as support computational research projects across the PBCI and collaborators within the University and Cambridge University Hospital. A such, the ability to work as part of a multi-disciplinary team and to be able to communicate to a range of audiences is required.

Join us in our mission to develop clinically useful algorithms, drive high-impact publications, and pave the way for personalised breast cancer treatments. Analyse data from cutting-edge technologies, collaborate with world-class researchers, and be part of a transformative journey. Apply now and be a catalyst for change in the global fight against breast cancer.

We welcome the opportunity to have a conversation and answer any questions you may have about the position and the PBCI. Please reach out to Prof Jean Abraham ( [e-mail] ) and Dr Joanna Worley ( [e-mail] ) to learn more about this exciting opportunity.

Fixed-term: The funds for this post are available until 31 August 2027 in the first instance.

This appointment requires a Research Passport application.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Research Associate (SRA) level; appointment as an SRA will require evidence of an independent research reputation. Due to the levels of skills and experience required we anticipate making an appointment either on the RA scale or towards the bottom of the SRA scale.

Approval of the Senior Research Associate is subject to Faculty Board approval.

Please ensure that you upload a covering letter and CV in the Upload section of the online application. The covering letter should outline how you match the criteria for the post and why you are applying for this role. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application.

Please include details of your referees, including email address and phone number, one of which must be your most recent line manager.

Closing date: 22nd June 2025

Interview date: between 30th June - 11th July 2025

Please quote reference RD46031 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity, and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
Further information

• Further Particulars