Research Associate in Computational Pathology and Multi-omic Data Integration (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 also become a member of the Mark Foundation Institute for Integrated Cancer Medicine and the Cancer Research UK Cambridge Centre.

This role is an exceptional opportunity to join a strong and passionate interdisciplinary team to develop new deep learning approaches to model the multi-scale spatial evolution of ovarian cancer. The successful candidate will drive the development and application of computational pathology methods to quantify tumour heterogeneity across multiple locations and time points. They will also create frameworks to discover and model spatial correlations with other data modalities such as genomics, transcriptomics, and radiological imaging. The research will aim to reveal new scientific insights into the disease as well as to provide support to critical, unsolved clinical questions.

The Research Associate will be supervised by Dr Mireia Crispin-Ortuzar, in close collaboration with a highly dynamic group of oncologists, radiologists, mathematicians, and computer scientists from across the University. In addition, the successful candidate will be part of the partnership between the University, Cambridge University Hospitals NHS Foundation Trust and GE Healthcare to deliver better patient outcomes across the East of England Cancer Alliance, by working together to solve unmet needs in care pathways of challenging cancers such as Ovarian, Renal and Breast. The partnership's overall aim is to develop a robust clinical data ecosystem to enable the deployment of AI solutions based on data integration.

Duties include developing and conducting research objectives, proposals and projects, with guidance and support from mentors. 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 and grow an internal and external network of 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.

https://www.jobs.cam.ac.uk/job/38078/