Clinical Decision Support System for Skin Monitoring & Melanoma Detection using Machine Learning

Here is an exciting opportunity to study a Machine Learning and Advanced Image Processing which could lead to entirely new approaches in skin monitoring and melanoma detection.

The selected candidate will apply their computer science and programming skills and ambition to create a clinical decision support system for the early recognition and treatment of malignant lesions on the basis of evaluations of clinical parameters. This multidisciplinary project, will allow the student to develop transferable knowledge and skills in this most exciting and active field of Machine Learning research.

This Knowledge Economy Skills Scholarship (KESS) project will be held in the Faculty of Computing, Engineering and Science at the University of South Wales. KESS is a programme funded by the European Social Fund (ESF) awarded by the Welsh European Funding Office (WEFO) in the Welsh Government. The PhD will be associated with the REU Clinical Bioinformatics team, Cardiff and Vale University Health Board headed by Professor Colin Gibson. The project will provide a student with an opportunity to access an anonymised database containing thousands of clinical datasets with medical diagnoses and descriptive information given by a group of expert dermatologists. This technology has the potential to drive improvements in health and well-being of patients by enabling more accurate skin monitoring and diagnosis.

The project is backed by the Institute of Dermatology, University Hospital of Wales, Cardiff represented by Dr Richard Motley. Dr Motley is the Chairman of the Speciality Training Committee for Dermatology in Wales, which oversees the training of Dermatologists in Wales and he has pioneered the teledermatology service in Cardiff.

Programme of research:

Diagnostic models have been studied in several medical disciplines to improve quality of patient care. However, recent advances in Machine Learning and Knowledge Based Systems combined with dramatic improvement in computer processing power available at low cost have opened new avenues for improvement in personalized learning and diagnosis systems. PhD student will investigate the feasibility of developing a diagnostic system that would exploit knowledge and skills specific of each physician and enable the sharing of experts’ clinical experience. Such a software tool should support the early recognition and treatment of malignant lesions on the basis of evaluations of clinical parameters. The novel approach involves creating a model tailored to each physician, combining the human expertise with computer analysis. The obtained results should outperform standard image processing approaches in early recognition of malignant lesions.

Studentship:
The studentship will cover the fees for a full-time PhD programme and pay a stipend of circa £14k p.a. There is also around £9k project support costs available for consumables, travel, minor equipment, training (including the KESS Grad School) and conference attendance.

The position is available from 1st April 2019.

Eligibility of Student:
To be eligible to hold a KESS studentship, you must:
• have a home address in East Wales area (details below)* at the time of registration.
• have the right to take up paid work in the East Wales area* on completion of the scholarship.
• be classified by the University as ‘home’ or ‘EU’ for tuition fees purposes according to the University’s guidelines.
• satisfy University of South Wales’s admissions criteria: see below, qualifications and experience and application process

* East Wales area covers: Vale of Glamorgan / Cardiff / Newport / Monmouthshire / Powys / Wrexham / Flintshire

Qualifications and experience:

Eligible applicants will:
• Have a degree (2i or higher) in an appropriate computing-related discipline
• Possess a reasonable understanding of computer programming.
• Be highly self-motivated, with capacity to learn and develop data analysis and machine learning techniques
• Have well-developed and positively collaborative interpersonal skills
• Have an ability to deliver technical reports and communicate findings
• Be willing to travel and work in clinical settings

Application Process:

To download an application package, please visit: https://gradschool.southwales.ac.uk/thinking-applying/specific-funded-studentships/

For any queries on eligibility, please contact: KESS Team at Research and Innovation Services, University of South Wales: [Email Address Removed] Tel: 01443 482578

For informal enquiries or further programme information, please contact: Dr Janusz Kulon [Email Address Removed].

Further information at:
https://at-web1.comp.glam.ac.uk/KBS/research.php