|Funding for:||UK Students, EU Students|
|Placed On:||21st May 2019|
|Closes:||19th August 2019|
Project title: Intelligent control of electronic systems with machine learning for micro plasma chemistry
Plasma chemistry is an emerging area crossing the boundaries of electrical engineering, physics and chemical engineering that offers exciting possibilities for generating a range of chemicals. Applications range from ozone generation for water treatment to the disposal of harmful waste products. The plasmas are formed using a high voltage excitation waveform, but applications are presently limited by lack of understanding of the link between the excitation waveform and the resulting chemical pathways. This project involves the development of novel plasma generation, control and instrumentation systems to facilitate new and exciting chemistry. Alongside traditional chemistry modelling techniques, machine learning will be used to gain further understanding of the processes involved. LabVIEW will be used for instrumentation and control, and excitation will be produced by power electronic inverters.
The studentship is available for a period of up to 3.5 years at the standard RCUK rate which covers UK/EU fees and includes a non-taxable stipend at the standard RCUK rate (£15,009 for 2019/20). A budget for IT equipment, training and attending conferences is also included.
The candidate will work alongside existing research teams in the Electrical Machines & Drives Research Group (led by Prof Martin Foster and Dr Jonathan Davidson) and the Department of Chemical Engineering (led by Prof Will Zimmerman).
Entry requirements and eligibility
The applicant should have, or expect to obtain, a first class or an upper second class honours degree, MSc (merit or distinction) or equivalent in electronic/electrical engineering, physics or a related discipline. Candidates should fulfil eligibility criteria for RCUK funding through UK/EU nationality and residency status. Further details regarding eligibility can be found on EPSRC’s web pages http://www.rcuk.ac.uk.
Enquiries and applications:
Applications should be made using the University’s online application system which can be found at the following web address:
On the application form please state Prof Martin Foster and Dr Jonathan Davidson as your preferred supervisors and state the project title as “Intelligent control of electronic systems with machine learning for micro plasma chemistry”
All inquiries should be addressed to Prof M. P. Foster (email@example.com), Department of Electronic & Electrical Engineering, The University of Sheffield, 3 Solly Street, Sheffield S1 4DE, UK.
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