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Clinical and biobank data integration by employing human-centred AI. A precision oncology approach to the diagnosis of prostate cancer

   Cardiff School of Engineering

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  Dr C Fuentes, Dr Dimitris Parthimos, Prof Emiliano Spezi, Dr Y Hicks  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Healthcare innovation becomes ever more dependent on emerging technologies, such as AI and machine-human interaction to enhance patient-specific diagnosis and treatment. As emerging technologies (estimated to create £350 billion in technology-driven value by 2025) integrate into clinical practice, healthcare professionals will interact regularly with autonomous systems in decision making. Multiple data streams, such as lab-based measurements, genomic/bioinformatics and clinical imaging will require pre-processing by autonomous systems in order to support multidisciplinary teams in making critical decisions. 

In support of personalised healthcare delivery, this project aims to integrate clinical, laboratory and bio-bank data streams under a single platform that support the diagnostic process. Employing tools such as artificial intelligence, machine learning and expert machine-human interaction will establish data compatibility. This is a significant step towards precision medicine, focused on understanding patient variability. Moreover, population level data can inform disease prevention and treatment and the coordination of multiple stakeholders in establishing novel tailored preventive and therapeutic approaches [2].

Aims and objectives

By taking a human-centred AI design approach this project aims to explore and establish the most appropriate interfaces and interactions in support of precision oncology. We seek to understand the best design practices for novel human-machine interactive mechanisms that combine artificial and human intelligence to optimise decision making in patient-specific healthcare. Through this project we will:

  • Follow a human-centred AI approach to unpack the technological interactions used in precision oncology, particularly prostate cancer.
  • Examine suitability to integrate emerging technologies used for optimising interpretation and communication challenges in prostate cancer (e.g., autonomous systems – social assistive robots)
  • Co-create scenarios that reveal the opportunities for emerging technologies to address and support precision oncology challenges (i.e., communication, interpretation, and data translation). Particularly supporting multidisciplinary teams in clinical settings.
  • Prototype interactions with emerging technologies (social robots and autonomous systems) in the area of precision oncology

Materials and methods

This work will involve interdisciplinary work, conducting lab-based experiments, simulation. Data will be obtained from Cancer Bio-banks, laboratory legacy and bespoke cell culture experiments, clinical patient data supplied by our NHS partner institutions, and both clinical and laboratory imaging data.

Outline and timeline:

Year 1: Training in precision oncology understanding, literature review and background study.

Year 2: Design scenarios to identify opportunities for emerging technologies to optimise precision oncology following a human-centred AI approach, publish results.

Year 3: Develop, deploy and evaluate prototypes integrating contextual information, quantitative and qualitative data in precision oncology scenarios.

Year 4: Thesis writing and submission, further analysis, and publications.

Anticipated results

Publication in indexed peer review journals and conferences. This work will contribute to the area of HCI, HRI and Emerging technologies identifying how to enhance interactions with novel technologies in multidisciplinary complex healthcare settings such as precision oncology.


You will be embedded in the Cardiff University Interdisciplinary Training Hub (IDTH) across the Schools of Medicine, Engineering Computer Science and collaborate with scientists in CUBRIC. You will also have the unique opportunity to work in a multidisciplinary group comprising radiologists, surgeons, medical imaging engineers, cancer biologists and physicists. You will be trained by world-leading academics in the fields of cancer, engineering, physics, and image analysis.

Essential skills required: Good computational skills (i.e, Python, Jupyter Notebook) 

Desirable skills required: Machine learning tools, understanding of artificial intelligence principles and applications. General understanding of quantitative and qualitative methods, and experience/interest in conducting research in health care.

Student skills development

Research skills in data preparation. Transferable skills in data handling, data and image analysis, programming, team-working and communication with academics, NHS staff, patients, and the public. Academic skills in scientific writing, presentation, and teaching. A unique opportunity to benefit from the expertise and training offered from the Cardiff University IDTH.

How to apply:

Complete the online Cardiff University Post-Graduate Application Form at  Computer Science and Informatics - Study - Cardiff University

When completing your personal statement consider giving examples of your achievements in research related activities and examples of your achievements in non-research related activities. Describe why you have chosen this project and What do you hope to gain from doing a PhD with IPOCH?

Please quote funding reference IDHub-1 in your application and the project title 'Clinical and biobank data integration by employing human-centred AI. A precision oncology approach to the diagnosis of prostate cancer'

Applications should be received no later than Monday 30th January 2023.

Applicants will be selected for interview by Monday 6th February 2023.

Interviews held 13th – 17th February 2023.

Project starting date: April 2023 or June 2023.


Candidates should hold or expect to gain a first-class degree or a good 2.1 (or their equivalent) in Engineering/Computer Science/Bioengineering or a related subject. International students will also need to meet the English Language requirements of the programme. To be eligible for a full award a student must have no restrictions on how long they can stay in the UK.

EPSRC studentships are available to home and international students. International students will not be charged the fee difference between the UK and international rate. Applicants should satisfy the UKRI eligibility requirements. 

Cardiff University is committed to supporting and promoting equality and diversity creating an inclusive environment for all. We welcome applications from all members of the global community irrespective of age, disability, sex, gender identity, gender reassignment, marital or civil partnership status, pregnancy or maternity, race, religion, belief and sexual orientation.

We welcome applications for both full and part-time study and from candidates with non-traditional academic backgrounds. For further information about modes of study, please contact us.


Applicants are reminded to submit all relevant documents by the deadline. Due to the volume of applications received, incomplete applications will not be considered.

Short-listed applicants will be invited to interview. As part of the interview process, applicants will be asked to give a short presentation, answer a series of panel questions etc – as seen appropriate to the recruitment process.

Interviews are expected to take place remotely via Zoom/Teams with a possible second interview of shortlisted candidates in person. Applicants can expect to hear the outcome of their interview within two weeks.

Funding Notes

The studentship is for 3.5 years and covers tuition fees, an annual tax-free living stipend of £17,688 (subject to change) and includes access to a Research Training Support Grant (currently £4000).


[1]: Schwartzberg L, Kim ES, Liu D, Schrag D. Precision oncology: who, how, what, when, and when not?. American Society of Clinical Oncology Educational Book. 2017 May;37:160-9.
[2]: Rundo L, Pirrone R, Vitabile S, Sala E, Gambino O. Recent advances of HCI in decision-making tasks for optimized clinical workflows and precision medicine. Journal of biomedical informatics. 2020 Aug 1;108:103479.
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