Medical Research Scotland
PhD Studentship Award
This project is one of 15 four year PhD Studentships funded by Medical Research Scotland (http://www.medicalresearchscotland.org.uk) to be delivered jointly by the named University and Company. The Studentship will provide the first-class academic and commercial training needed to equip the successful candidate for a science career in an increasingly competitive market.
"Complex, image analysis derived big-data to stratify colorectal cancer patients" to be delivered by the University of St Andrews [Supervisors: Dr Peter Caie and Professor David Harrison (School of Medicine)] and Indica Labs Ltd (http://www.indicalab.com) [Company supervisor: Dr Kate Lillard].
We offer a fully funded 4 year PhD studentship based in the Quantitative and Digital Pathology team within the School of Medicine. The Studentship is supported by an industry partner called Indica Labs which produces pathology based image and data analysis software. The PhD will be focused in the field of personalised pathology. The project will utilise cutting edge digital pathology and image analysis methodology to extract detailed and complex information from a patient’s heterogeneous and heterotypic tumour microenvironment. This image based data will be incorporated with molecular pathology and clinical data forming a personalised big data fingerprint for each patient. This big data will be analysed and mined through novel machine learning and statistical models to identify the optimal combination of multi-omics parameters to best answer the clinical question:
Which are the optimal clinically transferable and personalised parameters to identify colorectal cancer patients at a high risk of disease specific death?
For colorectal cancer (CRC) a clinical decision is based on the Tissue, Node and Metastasis (TNM) staging system. TNM staging is excellent at the prediction of disease progression across patient populations, however, it is less successful at predicting the outcome of an individual. It is imperative to identify individual CRC patients at a high risk of disease specific death to direct their optimal treatment plan.
The invasive front of a CRC tissue section is of particular prognostic value. The CRC microenvironment at the tumour to stroma interface consists of a complex milieu of histopathological features and heterotypic cellular interactions; some of which have been correlated to poor prognosis. CRC is a highly heterogeneous and complex disease and the reporting of single features may not be adequate to understand the aggressiveness of an individual’s cancer.
The candidate will receive training in clinical, digital and molecular pathology as well as in statistics, PhD thesis skills, generic research and career development which will help further their career prospects. They will have access to, and be fully trained in, both Indica Lab’s image analysis software and their novel informatics tools. The candidate will receive a unique experience to learn from and work within a medical, academic and commercial setting from both the University and industry partner (Indica Labs).
Enquiries should be sent by email to Dr Peter Caie: [email protected]
Candidates must have obtained, or expect to obtain, a first or 2.1 UK honours degree, or equivalent for degrees obtained outside the UK, in an appropriate discipline (an understanding of cancer and a background in image analysis or mathematical/statistical modelling will be advantageous).
Applications MUST be submitted through the University of St Andrews’ online application system at the following link. Applicants should include a covering letter with their online application, explaining why they wish to carry out this project.
Interviews are expected to take place 3-4 weeks after the closing date for applications.
It is anticipated that the PhD Studentship will start in September 2016.