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Clinical Research Associate: Cancer Imaging

Department of Radiology

University of Cambridge, Trinity Ln, Cambridge, UK


  • Posted on: 04th Nov 2021
  • Salary: £34,563-£59,845
  • REF: RQ28859
  • Closes: 28th November 2021
  • Contract Type: Fixed-Term/Contract
  • Hours: Full Time

The University of Cambridge, Department of Radiology is looking to recruit an Clinical Research Associate to support a collaborative group studying the role of advanced imaging techniques in patients with cancer.

The project is part of a CRUK, International Alliance for Cancer Early Detection (ACED) collaboration with the department of mathematics at University College, London (UCL). The proposal aims to amalgamate mathematical modelling skills developed at UCL with the clinical and academic expertise of Cambridge prostate cancer researchers to develop a personalised tool for continuous re-evaluation of risk of prostate cancer progression on active surveillance (AS).

Integral to this is the curation of a comprehensive time-series database of patients with biopsy-proven prostate cancer enrolled on AS containing a range of standard-of-care clinical and radiological biomarkers, coupled with histopathological evidence of disease progression. Cases will be subsequently divided into equally robust training, test and validation datasets. The subsequent UCL model will employ Method of Mean Trends (MMT), Bayesian Change-Point Model (BCP), and Deep Learning with Recurrent Artificial Neural Networks methodology to provide an accurate baseline estimate of the risk of short- and medium-term prostate cancer disease progression and enable a dynamic re-evaluation of the risk of disease progression based on serial biomarker change-point analysis at follow-up.

The Clinical Research Associate will work alongside an experienced consultant uro-radiologist to segment prostate gland and lesion/s where required, collate and evaluate data with senior support, including curating a multi-time point database incorporating clinical, radiological, and histopathological data. They will also participate in the development of research protocols and perform analysis and interpretation of results, and preparation of manuscripts for publication.

Applicants should be medically qualified, have (or be eligible for) full GMC registration and have FRCR or equivalent. Prior experience in tumour segmentation and image interpretation is essential. Candidates are expected to have a CV with the intention to follow an academic career in imaging research.

Informal enquiries may be directed to Dr Tristan Barrett (tb507@medschl.cam.ac.uk)

This is an integrated appointment between the University and Cambridge University Hospitals NHS Foundation Trust (“NHS Trust”). You will therefore also be issued with an Honorary Clinical Contract by the NHS Trust. You should be aware that if your contract with the NHS Trust is terminated your employment with the University will be terminated, and vice versa.

Fixed-term: The funds for this post are available until 31 December 2022 in the first instance.

This appointment requires an Honorary Clinical Contract.

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

Closing Date: 28th November 2021

Please ensure that you upload a covering letter, CV and a completed Additional Information for Clinical Researchers form in the Upload section of the online application. 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.

Please quote reference RQ28859 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

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