71 web-programmer-developer-"https:" "https:" "https:" "https:" "https:" "Medical Research Council" PhD positions at University of Nottingham
Sort by
Refine Your Search
-
A Design Methodology for Embedding Robotics & Automation into Circular Product Development This is an exciting opportunity to undertake industrially linked research in partnership with
-
are seeking a Ph.D. student to join our multidisciplinary team developing a radical solution for better detection and treatment that uses ultra-thin snake-like robots and advanced optical imaging techniques
-
, the wider industrial adoption of ASDs remains constrained. Current development pathways are slow, labour-intensive, and require substantial quantities of material. Techniques such as hot-melt extrusion and
-
of ASDs remains constrained. Current development pathways are slow, labour-intensive, and require substantial quantities of material. Techniques such as hot-melt extrusion and spray drying are typically
-
Supervised by: Rasa Remenyte-Prescott (Faculty of Engineering, Resilience Engineering Research Group) Aim: Develop a comprehensive railway network delay propagation model capable of addressing a
-
PhD project: Modelling Resilience of Water Distribution Networks Supervised by Rasa Remenyte-Prescott (Faculty of Engineering) Aim: To develop an modelling approach for assessing water network
-
). This studentship will include a placement at Astra Zeneca, Cambridge and is part of a broader Medical Research Council Programme grant focused to understand mucus regulation in severe asthma. The project will
-
funding to enrol on this PhD. For students from China, you are encouraged to apply in partnership with the China Scholarship Council - more information can be found here: https://www.nottingham.ac.uk
-
to develop a comprehensive modelling and analysis approach for hydrogen systems, such as electrolysers and their BoP systems, in meeting some of the below challenges in: advanced diagnostics and prognostics
-
to the analysis of time series. In particular, the project will examine and develop methods that go beyond the Markovian paradigm. It will consider a range of time series data, focusing on those that show