Cambridge Centre for Research Associate in Machine Learning for Cancer Medicine (Fixed Term)
Department of Oncology
We invite applications for a postdoctoral Research Associate to work in the Department of Oncology at the University of Cambridge. The successful candidate will become a member of the EPSRC Cambridge Mathematics of Information in Healthcare Hub (CMIH) and the Integrated Cancer Medicine Programme of the CRUK Cambridge Cancer Centre, and will also be affiliated with the Radiogenomics and Quantitative Imaging Group.
This role is an exceptional opportunity to join a strong and passionate interdisciplinary team to develop new machine learning approaches to understand metastatic cancer using medical imaging and complementary multi-omics data. The successful candidate will have access to extensive, deeply curated metastatic cancer datasets and drive the development and application of data analysis and machine learning methods. The research will aim to reveal insights into the disease and to provide support to critical, unsolved clinical questions.
The Research Associate will work with Dr Mireia Crispin-Ortuzar (Dept. of Oncology) and Prof. Carola-Bibiane Schönlieb (Dept. of Applied Mathematics and Theoretical Physics), in close collaboration with a highly dynamic group of oncologists, radiologists, mathematicians, and computer scientists from across the University. You will also be able to collaborate with our close technology industry partners, and an interest in entrepreneurship and translating research to the clinical setting is highly desirable.
Duties include developing and conducting individual and collaborative research objectives, proposals and projects. The role holder will be expected to plan and manage their own research and administration, with guidance and support from mentors, and to assist in the preparation of proposals and applications to external bodies. Collaborative skills and enthusiasm for multidisciplinary work are essential: you must be able to communicate material of a technical nature to technical and clinical audiences alike, and be able to build internal and external contacts. You will also be expected to assist in the supervision of student projects, the development of student research skills, provide instruction and plan/deliver seminars relating to the research area.