Cape Peninsula University of Technology
Faculty of Engineering and the Built Environment (FEBE) Department of Electrical, Electronic, and Computer Engineering
POSTDOCTORAL RESEARCH FELLOWSHIP
Power Systems, Smart Grid and Distributed Energy Systems SANEDI Smart Grid Contract Research Project
About the Project The Department of Electrical, Electronic, and Computer Engineering (DEECE) in the Faculty of Engineering and the Built Environment (FEBE) at the Cape Peninsula University of Technology (CPUT), South Africa, invites applications from suitably qualified researchers for a Postdoctoral Research Fellowship. This position is funded through a contract research grant awarded by the South African National Energy Development Institute (SANEDI) under the Smart Grid Research Programme. The project focuses on advancing smart grid technologies within the South African energy context. Research areas include non-technical loss (NTL) detection, machine learning applications for power systems, distributed energy resource (DER) integration, electric vehicle (EV) charging impacts on grid stability, and artificial intelligence-driven load forecasting. The successful applicant will be based at CPUT and will play a central role in producing research outputs, contributing to postgraduate student development, and fulfilling SANEDI’s human capital development reporting requirements.
Fellowship Details Stipend
R250,000 per annum (tax-free)
Duration
12 months, renewable subject to satisfactory performance, funding availability, and institutional policy
Start Date
As soon as possible (targeted: June 2026)
Location
Department of Electrical, Electronic & Computer Engineering. Cape Peninsula University of Technology, Bellville, South Africa
Nature of Appointment
Fellowship (contract-based). This is not a permanent employment position. Fellows may not hold concurrent paid full-time employment.
Key Responsibilities •
Conduct original research in smart grid technologies, with a focus on non-technical loss detection, DER integration, EV charging impacts on voltage stability, and AI-driven load forecasting