-
Alistair John Application Deadline: 30 June 2024 Details This project will use careful control of additive manufacturing process parameters to improve the performance of rocket engines and injectors and
-
Details Many human interactions with objects and surfaces rely on perception of the tactile interface. This could be when gripping objects with hands, or controlling walking movements through the physical
-
this process of irradiation damage will change the properties of the alloys and perhaps limit their useful lives. In this harsh environment, the forces experienced by materials can cause them to slowly deform in
-
-reported levels of physical activity, fatigue, sleep, social participation, and health related quality of life in people who suffer stroke. 2) To investigate whether exercise (ReSTORe) or fatigue (RICFAST
-
; these are machine learning models trained to predict the output of the physical system but can be differentiated for training. This project will develop the use of machine learning methods, particularly neural
-
with age or is linked to particular medical conditions. Funding Notes 1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant Discipline. View
-
are able to overcome status conflict in these teams using an interaction process analysis methodology. Given the quantitative nature of this research, the successful candidate will have a very strong
-
-Tavani Application Deadline: 10 July 2024 Details Project description The research project aims to explore the complex process of transformative value creation within service ecosystems. Through
-
healthy controls. We will analyse associations of: a) mental health status, b) life-time traumatic stress load, c) life-style (diet, nutrient intake, physical exercise, smoking), d) immunological markers
-
require a 1st or 2:1 degree in Engineering, Physics, Mathematics or similar discipline with strong mathematical skills. You will join the Brown Group within the Department of Chemical and Biological