Exploration of the use of smartphone technology in personalised approaches to care in Idiopathic Pulmonary Fibrosis

Ulster University, United Kingdom

Updated: 3 months ago
Location: Coleraine, NORTHERN IRELAND

These scholarships will cover full-time PhD tuition fees for three years (subject to satisfactory academic performance) and will provide a £900 per annum research training support grant (RTSG) to help support the PhD researcher.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

Please note: you will automatically be entered into the competition for the Full Award, unless you state otherwise in your application.

The scholarship will cover tuition fees at the Home rate and a maintenance allowance of £19,000 (tbc) per annum for three years (subject to satisfactory academic performance).

This scholarship also comes with £900 per annum for three years as a research training support grant (RTSG) allocation to help support the PhD researcher.


Bentley CL, Powell L, Potter S, Parker J, Mountain GA, Bartlett YK, Farwer J, O'Connor C, Burns J, Cresswell RL, Dunn HD, Hawley MS. The Use of a Smartphone App and an Activity Tracker to Promote Physical Activity in the Management of Chronic Obstructive Pulmonary Disease: Randomized Controlled Feasibility Study. JMIR Mhealth Uhealth. 2020 Jun 3;8(6):e16203. doi: 10.2196/16203.

Quach S, Michaelchuk W, Benoit A, Oliveira A, Packham TL, Goldstein R, Brooks D. Mobile heath applications for self-management in chronic lung disease: a systematic review. Netw Model Anal Health Inform Bioinform. 2023;12(1):25. doi: 10.1007/s13721-023-00419-0. Epub 2023 Jun 6.

Menni C, Valdes AM, Freidin MB, Sudre CH, Nguyen LH, Drew DA, Ganesh S, Varsavsky T, Cardoso MJ, El-Sayed Moustafa JS, Visconti A, Hysi P, Bowyer RCE, Mangino M, Falchi M, Wolf J, Ourselin S, Chan AT, Steves CJ, Spector TD. Real-time tracking of self-reported symptoms to predict potential COVID-19. Nat Med. 2020 Jul;26(7):1037-1040. doi: 10.1038/s41591-020-0916-2. Epub 2020 May 11.


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