Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
of this project, please contact Prof. Tony McNally (T.McNally@warwick.ac.uk ) directly for further information. Essential and Desirable Criteria: 1 or 2.1 degree in Materials Science & Engineering, Chemical
-
to mechanical forces. We work with leading international groups on modeling and also conduct simulations at DTU. Our overarching goal is to understand and predict the mechanical behavior of metals during plastic
-
co-supervision of student projects) Profile A master's degree in engineering, environmental sciences, or physics. Strong interest in experimental fluid mechanics. Experience with experimental (fluid
-
-field methods) Multiscale mechanics and microstructure-property relationships Python/C++/Matlab-based simulation and data analysis Industry-facing research and technology transfer You will also benefit
-
the Advanced Production Engineering (APE) research group that deals with the development, optimization and implementation of advanced production technologies and manufacture processes with emphasis on mechanical
-
- or nanoengineering, material science, mechanical engineering or similar. Experience with cleanroom fabrication processes or additive manufacturing is highly beneficial. You are expected to have a keen interest in
-
to receive a first or upper-second class honours degree in Materials Science, Mechanical Engineering, Physics, or a similar discipline. A postgraduate master’s degree is not required but may be an advantage. A
-
opportunity to contribute to cutting-edge research aimed at understanding microbiome-driven mechanisms and developing novel strategies for disease prevention and treatment. You will collaborate with renowned
-
Closing Date: 15th September 2025 [23:59 GMT] Supervisor: Prof M. Sumetsky Prospective Start Date: 1 January 2026 Applications are invited for a Postgraduate studentship, supported by Aston
-
experimentation with Asst. Prof. Eli N. Weinstein. Your goal will be to develop fundamental algorithmic techniques to overcome critical bottlenecks on data scale and quality, enabling scientists to gather vastly