Md Shafiullah

King Fahd University of Petroleum & Minerals (KFUPM) is inviting applications for Direct and Regular PhD fellowship routes in the Control and Instrumentation Engineering Department. The opportunity is aimed at highly motivated candidates interested in energy systems, intelligent sensing, advanced control and digital technologies. Research themes include intelligent sensing and instrumentation for critical infrastructure, energy systems, industrial processes and oil and gas pipelines; advanced control and energy management for smart grids and net-zero energy buildings; digital twins, large language models and AI/ML for energy and data-center management; and predictive maintenance of energy assets such as electric machines, drives, electric vehicles and renewable energy systems. The Direct PhD route is available to applicants with a four-year bachelor's degree, while the Regular PhD route requires both bachelor's and master's degrees. Applicants should have relevant qualifications in Systems and Control Engineering, Energy Engineering, Process Control Engineering, Electrical Engineering or a related field, a minimum CGPA of 3.60/4.00 or equivalent, and at least one first-author Q1 journal or flagship conference publication. Relevant industrial experience is advantageous, and all KFUPM/CGIS admission and English-language requirements must be met. Candidates must complete two application steps. Submit the research-group interest form by 25 November 2026, then submit the official CGIS application during the 1 November–15 December 2026 application window. The final university deadline is 15 December 2026. The post identifies the opportunity as a fellowship but does not specify stipend or tuition details.

King Fahd University of Petroleum & Minerals (KFUPM), Saudi Arabia, is advertising a PhD Fellowship Opportunity for Spring 2027 in the Control and Instrumentation Engineering (CIE) Department. The research group led by Md Shafiullah is seeking motivated PhD candidates interested in control engineering , energy systems , smart grids , renewable energy integration , predictive maintenance , and AI/ML for energy applications . Specific topics include control and management of energy systems such as smart grids and net-zero energy buildings, grid integration and control of renewable energy resources, data-driven identification and control of flexible loads, predictive maintenance for assets in energy systems (machine drives, EVs, renewable energy systems), and machine learning methods for energy-system applications. Eligibility includes a B.Sc. or M.Sc. in Systems and Control Engineering, Energy Engineering, Process Control Engineering, Electrical Engineering, or a related field. Research or industrial experience in the relevant areas is preferred. Applicants must also satisfy KFUPM/CGIS admission requirements , including the university's language and other admission criteria. The poster also highlights minimum GPA expectations of 3.5/4.0 for the listed degree pathways. This is described as a competitive fellowship with limited openings . No stipend amount or full funding breakdown is provided in the post. Deadline: the group asks applicants to email their CV by 25 June 2026 , while the university application deadline is 30 June 2026 . How to apply: email your CV to [email protected] and CC [email protected] . Use the subject line: Your Name (Ph.D. Applicant for Spring 2027) . Check the CGIS website for admission details and submit the university application by the stated deadline.