PhD studentship: Artificial intelligence based early detection of signet ring cell carcinoma in hereditary diffuse gastric cancer patients

This is a unique opportunity for PhD study in the world-leading Cancer Research UK Cambridge Institute (CRUK CI), to start a research career in an environment committed to training outstanding cancer research scientists of the future. The Institute has excellent state-of-the-art facilities and research ranges from basic biology and computational biology through to translational cancer research and clinical application.

Postgraduate students play a pivotal role in the continuing success of our research programmes. If you are interested in contributing to our success, please find further information at: https://www.cruk.cam.ac.uk/jobs-and-studentships/postgraduate-study

Professor Florian Markowetz wishes to recruit a student to work on the project entitled: Artificial intelligence based early detection of signet ring cell carcinoma in hereditary diffuse gastric cancer patients

This project will be co-supervised by Dr. Massimiliano di Pietro, a consultant gastroenterologist at Addenbrookes' hospital.

For further information about the research groups, including their most recent publications, please visit their website:
www.cruk.cam.ac.uk/research-groups/markowetz-group/ www.earlycancer.cam.ac.uk/dr-massimiliano-di-pietro/

Project details

Hereditary diffuse gastric cancer (HDGC) is a syndrome predisposing individuals to gastric cancer linked to mutation of the e-Cadherin gene (CDH1). Guidelines recommend prophylactic surgery with the view to prevent disease specific mortality, however a gastrectomy is linked to significant morbidity and impacts negatively to quality of life. Therefore, recently endoscopic surveillance has been proposed to assess the level of risk and detect early cancer, so that the best timing of prophylactic surgery is decided. Early signet ring cell carcinoma, however, is difficult to diagnose on standard endoscopy as the endoscopic features are very subtle. There is variation in practice in the pathological yield of biopsies even among expert centres. The aim of this project is to test and validate machine learning and deep learning methods to improve the diagnosis of early cancer in individuals with HDGC. This project is expected to lead to the development of an AI system that can assist the physician to diagnose early signet ring cancer, with high accuracy, during endoscopic surveillance of individuals with HDGC, ultimately improving the diagnosis of of sporadic gastric cancer.

Preferred skills/knowledge

We welcome applicants from both a computational or clinical background. Preferably, applicants have prior experience in computer programming and be familiar with data analysis, especially imaging data, in a programming language used for deep learning such as Python, including libraries such as Scikit-learn or PyTorch, and be passionate about the application of AI in clinical practice.

References/Further reading (optional)

Funding

This four-year studentship is funded by Cancer Research UK and includes full funding for University and College fees and, in addition, a stipend currently of £21,000 per annum for 4 years.

Eligibility

No nationality restrictions apply to Cancer Research UK studentships. Applications are invited from recent graduates or final year undergraduates who hold or expect to gain a first/upper second-class degree (or equivalent) in a relevant subject from any recognised university worldwide. Applicants with relevant research experience gained through Master¿s study, or while working in a laboratory, are strongly encouraged to apply.

How to apply

Please apply using the University Applicant Portal. For further information about the course and to access the applicant portal, go to:
https://www.postgraduate.study.cam.ac.uk/courses/directory/cvcrpdmsc Please select to commence study in Michaelmas Term 2024 (October 2024).

To complete your online application, you will need to provide the following:

Reference Request

The names and contact details of two academic referees who have agreed to act on your behalf.

Course Specific Question

Your statement of interest (limit of 2,500 characters) should explain why you wish to be considered for the studentship and which qualities and experience you will bring to the role.

Supporting Document

Please upload your CV (PDF file).

Deadline

The closing date for applications is 31 March 2024 with interviews expected to take place in mid to late May.

Please quote reference SW40762 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.