Cambridge Centre for Research Assistant (Fixed Term)
Cancer Research UK Cambridge Institute
The VISIONLab, led by Dr Sarah Bohndiek, uses next-generation imaging sciences to advance our understanding of tumour evolution. We create new imaging technologies, and combine them together with computational models, to study cancer in both mouse models and patients. The VISIONLab is co-located in the Department of Physics and the Cancer Research UK Cambridge Institute at the University of Cambridge, offering the opportunity to work in varying environments.
We are searching for a research assistant to support the work of our diverse international team in striving to create new methods that can help us to detect cancer earlier. Candidates with a strong background and interest in data science, particularly image analysis and a curiosity about science that extends across disciplines are likely to find this position rewarding, as it affords an opportunity to make an impact on our research by supporting both physicists and engineers, as well as biologists, to make a difference to human health. There are ample opportunities within the lab and the wider environment for personal and professional development and to help shape the course of research projects.
The successful applicant will be responsible for creating and maintaining image data analysis pipelines relevant across the broad range of imaging modalities used in the laboratory. These data will be 'hyperspectral', containing both spatial and spectroscopy information and requiring careful pre-processing prior to input into classification algorithms. The applicant will have access to a unique range of these different optical imaging data sets emerging from the team and will also be expected to curate previously acquired data sets for publication in support of the open-science mindset of the VISIONLab. Importantly, they will have the opportunity to lead on their own image analysis focused research project.
Applicants should have a bachelor's degree in physical sciences, engineering or a related area. They should have relevant experience in programming, ideally in Python or Java. Experience in statistical analysis or machine learning is desirable. Hands-on knowledge of creating hardware control interfaces e.g. for Arduino would be advantageous, as would direct experience of using ImageJ/Fiji. An interest in data visualisation is desirable.