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PhD Studentship: The numerical modelling of small-scale ocean processes by integrating deterministic and artificial intelligence techniques

University of Plymouth

Qualification Type: PhD
Location: Plymouth
Funding for: UK Students, EU Students
Funding amount: £14,777 per annum
Hours: Full Time
Placed On: 11th October 2018
Closes: 19th October 2018

Director of Studies:  Prof Georgy Shapiro

2nd Supervisor:         Dr Sanjay Sharma

3rd Supervisor:          Dr Jose Ondina

Applications are invited for a three-year PhD studentship. The studentship will start on 1 January 2019.

Project Description

A 3D ocean modelling at small scales is necessary to get correct and timely information of the changes incurring to ocean environment in order to predict the large catastrophic disturbances and take preventive actions to protect the equipment and human life, in particular in the coastal zones of the ocean. However, high resolution numerical modelling using current deterministic approach requires processing of huge amount of data in real-time and put significant stress on computational resources. For example, the doubling of a 3D model resolution requires a 10-fold increase in computing resources.

Modern artificial intelligence (AI) methods are successfully used in medical research and engineering. The use of AI methods allows combining the benefits of the deterministic approach (solving the equations of motion ) and the statistical approach based on the empirical relationship of the model inputs and outputs. However, despite the great popularity of the AI methods in many fields, there are some obstacles to adapting this to oceanography in a simple or straightforward way.

The aims of this PhD are

1) testing a hypothesis that the AI methods can be used in high-resolution 3D ocean modelling.
2) development of an advanced processing technique based on AI methods in order to obtain a fast and efficient model of the small  scale ocean processes.
3) simulation of high resolution ocean processes using a combination of a 3D deterministic and AI techniques.

The feasibility of the project is supported by both human (expertise of the supervisory team) and computing (HPC cluster) resources.

Eligibility

Applicants should have (at least) a first or upper second class honours degree in an appropriate subject and preferably a relevant MSc or MRes qualification.

The studentship is supported for 3 years and includes full Home/EU tuition fees plus a stipend of £14,777 per annum.  The studentship will only fully fund those applicants who are eligible for Home/EU fees with relevant qualifications.  Applicants normally required to cover overseas fees will have to cover the difference between the Home/EU and the overseas tuition fee rates (approximately £10,610 per annum).

If you wish to discuss this project further informally, please contact Prof Georgy Shapiro. However, applications must be made in accordance with the details shown below.

General information about applying for a research degree at University of Plymouth is available at: https://www.plymouth.ac.uk/student-life/your-studies/doctoral-college/applicants-and-enquirers

You can apply via the online application form which can be found at: https://www.plymouth.ac.uk/study/postgraduate and click ‘Apply’.

Please mark it FAO Ms Aimee McNeillie and clearly state that you are applying for a PhD studentship within the School of Biological and Marine Sciences.

For more information on the admissions process contact Ms Aimee McNeillie.

The closing date for applications is 12 noon on 19 October 2018. Shortlisted candidates will be invited for interview within 2 weeks. We regret that we may not be able to respond to all applications.  Applicants who have not received an offer of a place by mid November 2018 should consider their application has been unsuccessful on this occasion.

   
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