Postdoctoral Research Fellowship: Computational Sciences at University of Fort Hare

• Applications are invited for a Postdoctoral Research Fellowship in the Department of Computational Sciences under the discipline of Physics at the University of Fort Hare, under the supervision of Prof Patrick Mukumba. The fellowship forms part of an active research programme focusing on advanced wind energy technologies, with particular emphasis on low-wind-speed energy harvesting, including ducted wind turbine systems, concentrator-diffuser augmented wind turbines (CD-AWTs), INVELOX systems, shrouded wind turbines, and other innovative wind energy concepts. The research programme also encompasses offshore wind resource assessment, offshore wind turbine innovation, wind resource characterisation using ZX Wind LiDAR technology, and the design and optimisation of renewable energy mini-grid systems. A strong emphasis is placed on the application of Artificial Intelligence (AI), machine learning, computational fluid dynamics (CFD), digital modelling, and advanced optimisation techniques to improve wind resource assessment, turbine design, system performance, and decision-making for next-generation wind energy technologies.

ELIGIBILITY CRITERIA

• Applicant must have completed doctoral degree within the last five years.
• Must have graduated with a PhD in Renewable Energy, Mechanical, Mechatronics, Aerospace, or Electrical Engineering, Applied Physics, or a closely related field.
• Should have demonstrated expertise in wind energy systems, wind resource assessment, and renewable energy mini-grid design and performance optimisation.
• Experience in Computational Fluid Dynamics (CFD), Artificial Intelligence (AI), machine learning, and numerical modelling for wind energy applications will be a distinct advantage

THE SUCCESSFUL CANDIDATE WILL BE REQUIRED TO:

• Conduct innovative research on advanced wind energy technologies for low-wind-speed energy harvesting.
• Develop, model, and optimise wind turbine systems using Computational Fluid Dynamics (CFD), Artificial Intelligence (AI), machine learning, and advanced optimisation techniques.
• Conduct wind resource assessment and characterisation using the ZX Wind LiDAR system for onshore and offshore wind energy applications.
• Design, construct, install, and experimentally evaluate innovative wind energy augmentation systems, including ducted, shrouded, concentrator, diffuser, and INVELOX-based technologies for both horizontal-axis and vertical-axis wind turbines.
• Contribute to the design and optimisation of renewable energy mini-grid systems integrating wind energy technologies.
• Contribute to the research productivity of the research group, postgraduate students as well as the Department.
• Must produce a research publication unit of 2.0 per annum with the host.

FELLOWSHIP VALUE AND DURATION

• The fellowship is valued at R300,000 per annum (tax-free).
• The initial appointment will be for 24 months, subject to the University's Postdoctoral Research Fellowship Policy.
• Renewal beyond the initial appointment period will be based on satisfactory performance and achievement of the required research outputs.

Deadline:9th October,2026