Next generation additive manufacturing using laser diode arrays
A funded PhD Studentship (UK/EU only) is available for research into next-generation additive manufacturing processes based on a new method for selective laser melting. The approach, pioneered in Sheffield, is based on diode area melting using multiple arrays of relatively low power laser diodes for efficient, scalable, high-speed parallel processing of powdered feedstock and the creation of 3D net-shape components.
The successful applicant will gain expertise in the design and customisation of optoelectronic modules, integrated optics, and materials processing. The Studentship will be based within the Department of Electronic & Electrical Engineering, which is currently host to the EPSRC National Epitaxy Facility , a world-class facility for the growth of a range of semiconductor materials. In addition, the team has access to a state-of-the-art device fabrication cleanroom facility an extensive range of optoelectronic characterisation facilities. Dept of Mechanical Engineering, a broader skillset will be developed, with the student engaged in materials processing and metallurgy. Furthermore, the student will work alongside colleagues across the Engineering Faculty (Mechanical and Materials), further broadening their skill-set.
Apply online at https://www.sheffield.ac.uk/eee/pgr/apply
Funding is available for UK and EU students only. Awards for UK students cover tuition fees and a maintenance allowance for the project duration. EU applicants who have been resident in the UK for at least 3 years immediately preceding the start of their course are eligible for awards that cover tuition fees and provide a maintenance allowance. EU applicants that do not meet this residency criteria are eligible for a fees-only award.
Self-funded overseas applicants are welcome.
How good is research at University of Sheffield in Electrical and Electronic Engineering, Metallurgy and Materials?
Electronic and Electrical Engineering
FTE Category A staff submitted: 34.80
Research output data provided by the Research Excellence Framework (REF)
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