Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
Vickey, Dr K Lohwasser Application Deadline: Applications accepted all year round Details A position is open for an enthusiastic particle physics PhD student to conduct research in developing silicon
-
wave theory in inhomogeneous, expanding waveguides that have steady flows. Wave propagation and instability theory will be developed and applied to a number of solar structures from pores, magnetic
-
trenching, remoulding, and pore-pressure variation. This project will develop a new computational model to simulate seabed–mooring interaction at the particle scale. It will combine the Discrete Element
-
the discovery of spicules by Father Secchi about 150 years ago, a number of competing theories have been developed to model the generation, propagation and energy and momentum transport capabilities of spicules
-
Dr Marco Conte Application Deadline: Applications accepted all year round Details Developing sustainable alternatives to fossil fuels is one of the major challenges in modern chemistry. A promising
-
Jonathan Howse Application Deadline: Applications accepted all year round Details This PhD project aims to develop novel metrology techniques for thin flexible films made via a range on industrial
-
of the science departments at the University of Sheffield, you’ll be part of the Science Graduate School. You’ll get access to training opportunities designed to support your career development by helping you gain
-
team of multiple disciplines at the Integrated Manufacturing Group (IMG) to develop novel solutions for the high-value manufacturing sector, you will conduct research into specific technical fields
-
, modelling, software development, and data analysis. This PhD project will focus on addressing the short baseline anomalies through measurements of key parameters which govern sterile neutrino oscillations and
-
with the CDT’s aim to achieve a sustainable wind farm lifecycle by developing methods for high-value reuse of composite turbine blades. Machine learning and non-destructive evaluation techniques will be