Rakesh Mishra
1 year ago
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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
United Kingdom
University
University of Huddersfield
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About this position
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
United Kingdom
Research Interests
Fluid Mechanics
Energy Engineering
Thermal Engineering
Combustion Science
High-temperature Engineering
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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