Postdoctoral Wind Energy AI & CFD Research Fellow

University of Fort Hare; Oos-Kaap; On-site; ZAR 255,000 - 345,000; Full time

Job summary

University of Fort Hare invites applications for a Postdoctoral Research Fellowship in the Department of Computational Sciences, focusing on wind energy technologies, AI/ML, CFD, and advanced optimisation.

The position supports development of wind turbine systems and mini-grid design, with ZX Wind LiDAR resource assessment for onshore and offshore applications. The role spans 24 months and aims for high-impact publications.

Qualifications

• PhD completed within last five years.
• PhD in Renewable Energy, Mechanical, Mechatronics, Aerospace, Electrical Engineering, Applied Physics, or closely related field.
• Experience in wind energy systems, wind resource assessment, and renewable energy mini-grid design and performance optimisation.
• Experience in CFD, AI, ML, and numerical modelling for wind energy applications is advantageous.

Responsibilities

• Conduct innovative research on advanced wind energy technologies for low-wind-speed energy harvesting.
• Develop, model, and optimise wind turbine systems using CFD, AI, ML and advanced optimisation techniques.
• Conduct wind resource assessment and characterisation using ZX Wind LiDAR for onshore and offshore applications.
• Design, construct, install, and evaluate wind energy augmentation systems (ducted, shrouded, concentrator, diffuser, INVELOX) for horizontal- and vertical-axis turbines.
• Contribute to design and optimisation of renewable energy mini-grid systems.
• Contribute to research productivity of the research group and postgraduate students.
• Produce a research publication unit of 2.0 per annum with the host.

Skills

CFD

AI

Machine learning

Wind energy

Education

PhD in Renewable Energy/Mechanical/Mechatronics/Aerospace/Electrical Engineering/Applied Physics

Tools

ZX Wind LiDAR

CFD software

Job description

University of Fort Hare invites applications for a Postdoctoral Research Fellowship in the Department of Computational Sciences, focusing on wind energy technologies, AI/ML, CFD, and advanced optimisation.

The position supports development of wind turbine systems and mini-grid design, with ZX Wind LiDAR resource assessment for onshore and offshore applications. The role spans 24 months and aims for high-impact publications.