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CFD Jobs Database - Job Record #19592

Job Record #19592
TitleComputational and ML Modelling of Low Temperature Plasmas
CategoryPhD Studentship
EmployerDept Engineering Univ Exeter
LocationUnited Kingdom, Devon, Exeter
InternationalNo, only national applications will be considered
Closure DateFriday, March 28, 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.

Entry requirements
Applicants for this studentship must have obtained, or be about to obtain, a 
First or Upper Second Class UK Honours degree, or the equivalent qualifications 
gained outside the UK, in an appropriate area of Engineering, Physics or related 
disciplines.

If English is not your first language you will need to meet the English language 
requirements and provide proof of proficiency. 

Further details and application through the Uni web link; 
https://www.exeter.ac.uk/study/funding/award/?id=5497
Contact Information:
Please mention the CFD Jobs Database, record #19592 when responding to this ad.
NameDr Gavin R Tabor
Emailg.r.tabor@ex.ac.uk
Email ApplicationYes
URLhttps://www.exeter.ac.uk/study/funding/award/?id=5497
Record Data:
Last Modified22:22:02, Monday, March 03, 2025

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