Details
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.
More information on the English language requirements can be found here: https://www.sheffield.ac.uk/postgraduate/english-language
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 ([email protected]). Please add quote [PHD-robustAI] in the email subject line.
- Submit the full application to the University of Sheffield’s Postgraduate Online Application Portal (www.sheffield.ac.uk/postgradapplication/). Please name Professor Jungong Han as your supervisor (Dr Chen Chen will be starting at the University of Sheffield in November 2023, so isn't currently able to process applications on the system).
- 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.
Funding Notes
This studentship covers 3.5-year tuition fee (home fee rate) and a maintenance bursary. International students are welcomed to apply, but you must have the means to pay the difference between the UK and overseas tuition fees by securing additional funding or self-funding. Further information on International fees can be found here - https://www.sheffield.ac.uk/new-students/tuition-fees/fees-lookup.