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PhD Studentship in Robust and Adaptive AI for Medical Imaging and Precision Medicine

University of Sheffield

Qualification Type: PhD
Location: Sheffield
Funding for: UK Students, EU Students, International Students
Funding amount: £18,622 Funding will cover UK home tuition fees and a tax-free stipend at UKRI rate (£18,622 for 2023/24) for 3.5 years
Hours: Full Time
Placed On: 18th October 2023
Closes: 31st December 2023

A 3.5-year funded PhD studentship is available in the Department of Computer Science at University of Sheffield, working on the topic of robust and adaptive AI-enabled vision system for medical imaging and precision medicine. 

About the project

The field of medical imaging and precision medicine has seen remarkable advancements in recent years, driven by the potential of artificial intelligence (AI) technologies, such as transformers, powerful foundation models, multi-modal learning algorithms, and large language models [1]. These technologies can revolutionize healthcare by enabling accurate diagnosis, personalized treatment planning, and improved patient outcomes. This project will focus on developing robust and adaptive AI models that can handle the complexities of medical imaging data as well as the domain gap and knowledge gap across different scenarios, and further adapt to individual patient needs. Depending on the profile of the student, a particular focus would be identifying pitfalls of current AI models with adversarial machine learning techniques and/or explainable AI (XAI) to enhance the reliability and applicability of AI algorithms for healthcare applications. 

The starting date for this position is negotiable, preferred to be in Feb. 2024, or Sep. 2024. 

[1] Moor, M, et al. Foundation models for generalist medical artificial intelligence. Nature, 2023 

About the Department and Research Groups

The successful candidate will join the Computer Vision group in the Department of Computer Science, led by Prof. Jungong Han. As a PhD candidate, you will have access to state-of-the-art facilities, extensive resources, AI-focused community (https://shef-ai.github.io/) and a collaborative research ecosystem, incl. partnerships with Insigneo —the largest institute in Europe dedicated to in silico medicine technologies (www.sheffield.ac.uk/insigneo). 

Candidate requirements

  • Being self-motivated and enthusiastic about doing research in AI for healthcare and a commitment to supporting high quality research.
  • Have a good first degree in computer science, statistics, physics, engineering, or any-related field.
  • Experiences with AI for healthcare related projects using PyTorch and/or TensorFlow libraries.
  • Strong programming skills such as Python, C++, C, Java are preferred.
  • Excellent oral and written communication skills.
  • Strong problem-solving abilities.
  • Experiences of presenting or preparing scientific manuscripts in journals or conferences is preferred.

Information on the English language requirements can be found here: https://www.sheffield.ac.uk/postgraduate/english-language 

Funding information

3.5 years studentship covering UK home fees only (overseas applicants are welcome to apply, but they must be able to fund the difference between home fees and overseas fees themselves/through additional funding). 

How to apply

  • Enquiries and applications including a letter of interest, an up-to-date CV and transcripts should be sent to Dr Chen Chen (work.cherise@gmail.com). Please add quote [PHD-robustAI] in the email subject line.
  • Submit the full application to the University of Sheffield’s Postgraduate Online Application Portal via the 'Apply' button above (www.sheffield.ac.uk/postgradapplication/). Please name Professor Jungong Han as your supervisor if applying before 1st November and Dr Chen Chen if applying after 1st November. You must include your CV, research proposal, two academic reference letters and proof of degree with transcripts. See http://www.sheffield.ac.uk/postgraduate/phd/apply/applying for more details.
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