About the Project
This exciting multidisciplinary research project, led by Professor Abdul Sadka, will research low-level image analytics and artificial intelligence (AI) for the automatic and accurate diagnosis of COVID-19 featuring in X-Radiography of the respiratory system. The derived features will be used to interpret X-ray and automatically identify COVID-19 cases from other types of upper respiratory tract infections such as sore throat, and lower respiratory tract infections such as asthma and lung cancer etc., making it an adaptive feature-based disease identification and classification solution.
In the second phase of this doctoral project, the AI-driven diagnosis of X-ray features of lung infections will be combined with the functional and physiological biomarkers of respiratory function, in order to define more accurately the disease severity level and tailor a specific therapeutic programme for individual patients. Augmented reality (AR) combined with deep neural network-based tracking of respiratory behaviour will allow the design of a tailored respiratory biofeedback rehabilitation programme. By investigating the integration between physiological and AI-driven diagnostics, this project will pave the way towards improving the therapeutic programme of COVID-19 cases.
Applicants will have or be expected to receive a first or upper-second class honours undergraduate degree in Engineering, Computer Science, Design, Mathematics, Physics or similar discipline. A postgraduate (Masters) degree is not required but may be an advantage. You must be eligible for home tuition fees either through nationality, residency (living in the UK for at least three years and not wholly for educational purposes) or other connection to the UK.
Applicants will be required to demonstrate programming aptitude and their ability to undertake Modelling & Simulation under various experimental conditions and in diverse settings. In addition, he/she should be highly motivated, have research project experience and have the desire to work in an inter-disciplinary team, transcending traditional engineering and clinical boundaries to develop novel and impactful methods for addressing critical public global health issues.
Contact InformationPlease, contact for an informal discussion about the studentships:
Professor Abdul Sadka: [email protected]
Professor Dido Green: [email protected]
Dr Marco Davare: [email protected]
How to ApplyPlease submit your application documents (see list below) by Noon on 1st October 2020 to
[email protected]. Interviews will take place as soon as possible.
• Your up-to-date CV;
• Your personal statement (300 to 500 words) summarising your background, skills and experience;
• Your Undergraduate/Postgraduate Masters degree certificate(s) and transcript(s);
• Evidence of your English language skills to IELTS 6.5 (or equivalent, 6.0 in all sections), if appropriate;
• Contact details for TWO referees, one of which can be an academic member of staff in the College.
Note: Please remember to state the title of the project at the top of your personal statement.
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