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[Sponsors] |
Job Record #19671 | |
Title | Computational and ML Modelling of Low Temperature Plasmas |
Category | PhD Studentship |
Employer | University of Exeter |
Location | United Kingdom, Devon, Exeter |
International | No, only national applications will be considered |
Closure Date | Monday, June 30, 2025 |
Description: | |
The University of Exeter and Oxford Instruments Plasma Technologies are offering a jointly funded PhD position in computational and machine learning modelling of low temperature plasmas. Oxford Instruments (OI) develops and markets a range of manufacturing and scientific equipment using low temperature plasmas for etching and deposition. Plasma is a complex state of matter which can be considered as a fluid or as individual particles; moreover, complex chemical reactions can occur between species in the plasma. Modelling a plasma is accordingly a very complex and challenging task. The objective of the project is to optimise the hardware for the control of plasma in an atomic layer deposition chamber using various computational modelling approaches. This will require a hybrid fluid/particle model, which will be developed using the OpenFOAM toolkit A modelling workflow will be created, and then used as the basis for the optimisation, potentially using tools such as Bayesian Optimisation. In addition, novel machine learning approaches will be investigated as a faster alternative for modelling the injector. The technological impact of this work will be quite significant. Plasma etching is an important stage in manufacturing of microprocessors and other electronic devices, and any advance in this manufacturing is likely to have significant benefits. Computational modelling such as is investigated here can be the key to more efficient manufacturing and enable OI to push the envelope of what is possible. The modelling being developed here also have significant applications in other areas of plasma research. The studentship will be awarded on the basis of merit. The project will involve computational modelling using physics- and machine learning-based methods and would suit a top student with a background in Physics, Engineering, Mathematics or similar disciplines with an interest in computer modelling. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee (~£24k) and no stipend. International applicants need to be aware that they will have to cover the cost of their student visa, healthcare surcharge and other costs of moving to the UK to do a PhD. The conditions for eligibility of home fees status are complex and you will need to seek advice if you have moved to or from the UK (or Republic of Ireland) within the past 3 years or have applied for settled status under the EU Settlement Scheme. The collaboration involves a project partner who is providing funding [and other material support to the project], this means there are special terms that apply to the project, these will be discussed with Candidates at Interview and fully set out in the offer letter. The collaboration with the named project partner is subject to contract. Please note full details of the project partner’s contribution and involvement with the project is still to be confirmed and may change during the course of contract negotiations. Full details will be confirmed at offer stage. Full details and application here: https://www.exeter.ac.uk/study/funding/award/?id=5497 |
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Contact Information: | |
Please mention the CFD Jobs Database, record #19671 when responding to this ad. | |
Name | Dr Gavin R Tabor |
g.r.tabor@ex.ac.uk | |
Email Application | Yes |
Phone | 07804147738 |
URL | https://www.exeter.ac.uk/study/funding/award/?id=5497 |
Address | Harrison Building North Park Road Exeter |
Record Data: | |
Last Modified | 16:26:28, Wednesday, May 07, 2025 |
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