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Fully Funded ADDED PhD scholarship: Data-driven modelling of thermally coupled fluids and hydraulic efficiency optimisation in pipe flows

College of Engineering

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Prof Antonio Gil , Prof M G Edwards No more applications being accepted Funded PhD Project (Students Worldwide)

About the Project

Start date: January 2021

Subject areas: Big Data; Machine Learning (ML); High-Performance Computing (HPC); Engineering Simulation; Computational Mechanics

The digital revolution offers an exciting opportunity to disrupt the engineering sector. There is a need to develop a national Data-Driven Engineering Design capability to bridge the Technology Readiness Level (TRL) gap across applications that are notoriously difficult and expensive to prototype. This will require a multidisciplinary community from Industry and Academia to bridge the disciplines of ML, HPC and Industry 4.0 technologies.

The goal is to establish a platform, which leads to systems and processes that are designed for data and designed by data. To do this, the design process must be turned on its head; it is no longer appropriate for designers to focus solely on the operational use as optimisation targets. As part of a circular economy, usage and monitoring across entire life-cycles must be the cornerstone of development. Current practice is to base design decisions for systems and processes on computational modelling or simulation that emulates expected utilisation scenarios to evaluate predicted performance. Research as part of the new ADDED Centre of Excellence will pursue an approach that focuses on data-based outcomes to project backwards how systems and processes should be utilised in order to inform optimal design, including:

Optimisation of data collection
Predictive monitoring of complex systems
Real-time simulation
Handling of anomalies and extreme events
Automation with ML from real-world data
Measured and simulated data-driven design of additive manufactured materials
We are calling for applications for 3-year fully funded and industrially sponsored research studentship as part of a new exciting initiative at The College of Engineering, Swansea University. The PhD research project is in the area of Computational Methods coupled with Machine (Deep) Learning and will focus on thermo-fluid dynamics and geometric optimization, particularly in pipe flows involving extreme temperature heat fluxes.

This training programme will offer an unparalleled opportunity to develop your skills in areas vital to Advanced Data-Driven Engineering Design. These include topics, such as: Big Data; Machine Learning; High-Performance Computing; Leading Edge Engineering Simulation of Systems and Processes; Advanced Computational Mechanics and Fluids and Additive Manufacturing, all of which are highly in demand by our industrial partners, thus putting you at the forefront of employability.

The successful candidate will have an undergraduate degree in a relevant subject, e.g. engineering, materials science, physics, computer science or mathematics. Previous specialisation in data-driven engineering is not required as the student will gain this expertise during their studies in addition to valuable transferable skills ensuring the candidate is prepared for a wide range of possible career paths after graduation.

Location: Zienkiewicz Centre for Computational Engineering & Future Manufacturing Research Institute, Bay Campus, Swansea University.

The centres are closely linked to a number of world-leading strategic partners in industry and academia such as Karlsruhe Institute of Technology (KIT), UK Atomic Energy Authority (UKAEA) and the Indian Institute of Technology (IIT) Madras. Depending on projects’ particular research focus, students will be provided opportunities to undertake placements for significant periods (e.g. 6 months) with our research partners.

Supervisors: Professor Antonio J. Gil and Professor Michael Edwards from the Zienkiewicz Computational Centre for Engineering. The project will be in collaboration with UK Atomic Energy Authority (UKAEA).

Candidates should hold a first or upper second-class honours degree (or its equivalent). A Master’s degree in a subject area related to the project (engineering, computer science, mathematics, physics and cognate disciplines) would be advantageous but not strictly necessary.

Experience with engineering simulation is desirable.

Good programming skills, Python, CUDA, C/C++ Fortran or MATLAB are preferred.

We would normally expect the academic and English Language requirements to be met by point of application. For details on the University’s English Language entry requirements, please visit –

This scholarship is open to candidates of any nationality.

Funding Notes

This scholarship covers the full cost of UK/EU/international tuition fees and an annual stipend of £15,009 - £20,000.

There will also be additional funds available for research expenses. The ADDED centre has an allocated budget which will cover training, cohort activities, equipment, travel, placements and conference attendance.

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