Publisher
source

Rakesh Mishra

1 year ago

Advanced design strategies for offshore horizontal-axis wind turbines University of Huddersfield in United Kingdom

Degree Level

PhD

Field of study

Machine Learning

Funding

The studentship is fully funded for 3 years, covering tuition fees and a tax-free stipend starting at £20,780 for 2025/26, increasing in line with EPSRC guidelines in subsequent years. Funded via the EPSRC Doctoral Training Programme. No funding is available for the 12-month writing-up period.

Deadline

Expired

Country flag

Country

United Kingdom

University

University of Huddersfield

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New Today

Keywords

Machine Learning
Environmental Science
Aerodynamics
Mechanical Engineering
Aerospace Engineering
Fluid Mechanics
Wind Energy
Energy Engineering
Aeroacoustics
Surrogate Modeling
Laboratory Experimentation

About this position

?? EPSRC DTP Funded PhD Studentship – UK Home Students Only
University of Huddersfield – School of Computing and Engineering
Centre of Thermofluids, Energy Systems and High-Performance Computing
?? Aligned with EPSRC’s "Engineering Net Zero" Strategic Priority
????? Supervisory Team:
Dr Hossein Fatahian (Principal Supervisor)
Professor Rakesh Mishra (Co-Supervisor)
?? PhD Project Title:
Advanced Design Strategies for Next-Generation Offshore Horizontal-Axis Wind Turbines
?? Project Overview:
We are offering a fully funded EPSRC Doctoral Training Partnership (DTP) PhD studentship for UK home students, focused on advancing the future of offshore renewable energy.
This project will develop a hybrid CFD–AI–experimental framework to optimize the aerodynamic and aeroacoustic performance of next-generation offshore wind turbine blades using cutting-edge flow control strategies.
Your research will focus on:
? High-fidelity CFD and LES-based blade design
? Integration of active/passive flow control techniques
? Surrogate modelling and AI-driven multi-objective optimization
? Wake structure characterization via Dynamic Mode Decomposition (DMD)
? Wind tunnel experiments for model validation
This is a highly interdisciplinary opportunity, combining fluid dynamics, machine learning, and experimental methods—directly supporting the UK’s Net Zero ambitions and offshore wind energy targets.
?? Ideal Candidate:
We are looking for a motivated and UK-based student with:
? A First Class or Master's degree in Mechanical Engineering, Aerospace Engineering, Renewable Energy, or related disciplines
? Strong background in fluid mechanics, aerodynamics, or wind energy systems
? Hands-on experience with CFD tools (e.g., ANSYS Fluent, OpenFOAM)
?? Desirable: knowledge of machine learning, surrogate modelling, MATLAB/Python, and experimental fluid dynamics
?? Start Date: October 2025
?? How to Apply:
Interested applicants should contact Dr Hossein Fatahian :
?? [email protected]
Or apply via the University of Huddersfield’s postgraduate portal:
?? https://lnkd.in/eM4EvHpj

PhDOpportunity EPSRC FundedPhD DTPStudentship UKPhD EngineeringPhD
WindEnergy RenewableEnergy NetZero CFD AIinEngineering OffshoreWind
SustainableEngineering

Funding details

The studentship is fully funded for 3 years, covering tuition fees and a tax-free stipend starting at £20,780 for 2025/26, increasing in line with EPSRC guidelines in subsequent years. Funded via the EPSRC Doctoral Training Programme. No funding is available for the 12-month writing-up period.

What's required

Applicants must be UK home students with a First Class or Master's degree in Mechanical Engineering, Aerospace Engineering, Renewable Energy, or related disciplines. A strong background in fluid mechanics, aerodynamics, or wind energy systems is required. Hands-on experience with CFD tools (such as ANSYS Fluent or OpenFOAM) is essential. Desirable skills include knowledge of machine learning, surrogate modelling, MATLAB/Python, and experimental fluid dynamics. Applicants should be highly motivated and of outstanding quality.

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Professors

Professor

University Name
Country flag

United Kingdom

Research Interests

Fluid Mechanics

Energy Engineering

Thermal Engineering

Combustion Science

High-temperature Engineering