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PhD Studentship: Machine learning in hydraulics and fluid mechanics

University of Southampton

Qualification Type: PhD
Location: Southampton
Funding for: UK Students
Funding amount: £17,668 For UK students, tax-free per annum for up to 3.5 years.
Hours: Full Time
Placed On: 6th February 2023
Closes: 31st August 2023
 

Applications are invited for a fully funded PhD position on machine learning (ML) applied to problems in hydraulics and fluid mechanics.

The ubiquitous use and advantages of various machine learning (ML) algorithms in many aspects of modern life is common knowledge. With applications ranging from speech and image recognition to chatbots and financial forecasting, the possibilities of benefiting from ML are endless. One such possibility is the use of ML to enhance, or potentially replace, models of fluid flow based on physical principles, which are routinely used to e.g. predict floods or coastal erosion (both important challenges in the context of climate change adaptation). Within this general theme, the selected candidate will have plenty of scope and freedom to define a specific problems to focus on during their PhD.

The successful applicant will join a world-leading research team and environment at the University of Southampton, a Russell Group member ranked as one of the world’s top 100 universities. Of particular importance for this project is the access to Iridis 5, the University of Southampton’s recently upgraded supercomputer, considered one of the most powerful in the UK.

This 3.5 years studentship covers UK level tuition fees and provides an annual tax-free stipend at the standard EPSRC rate, which is £17,668 for 2022/23. The funding available is competitive and will only be awarded to an outstanding applicant. As part of the selection process, the strength of the whole application is taken into account, including academic qualifications, personal statement, CV and references. Applicants should have a good first degree in mathematics, physics or a relevant engineering subject. Ideally, the candidate should have some experience in fluid dynamics/hydraulics and machine learning. The planned start date is Autumn 2023, but an earlier start is also possible.

If you wish to discuss any details of the project informally, please contact Dr Sergio Maldonado Water and Environmental Engineering Research Group, Emails: s.maldonado@soton.ac.uk; Tel: +44 (0) 2380 59 2662.

Entry Requirements

A very good undergraduate degree (at least a UK 2:1 honours degree, or its international equivalent).

Closing date: applications should be received no later than 31 August 2023 for standard admissions, but later applications may be considered depending on the funds remaining in place.

Funding: For UK students, Tuition Fees and a stipend of £17,668 tax-free per annum for up to 3.5 years.

Applications should include:

Curriculum Vitae

Two reference letters

Degree Transcripts/Certificates to date

For further information please contact: feps-pgr-apply@soton.ac.uk

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