38 distributed-computing-"Multiple"-"Humboldt-Stiftung-Foundation" PhD positions at University of Nottingham
Sort by
Refine Your Search
-
the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
-
the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
-
at Nottingham https://www.nottingham.ac.uk/coatings/ is an international reference for all Thermal Barrier Coating activities. This PhD programme, in partnership with Rolls-Royce, will address key challenges
-
Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading academics from 5 universities, and 11
-
Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after
-
of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging
-
suitable for a hard-working researcher with an interest in respiratory infections. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter
-
nationals only) and research costs) three-year full-time PhD available to start on the 1st October 2025. The overall theme of this PhD programme is improving clinical assessment and research access
-
research programme funded by the Academy of Medical Sciences Springboard award. This project aims to explore the role of these neighbouring glycoproteins in neurotrophin-mediated neuronal development as
-
a variety of machine learning algorithms trained on these data and, most crucially, will develop and implement techniques for computing the uncertainty in the prediction. The algorithms developed in