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Ghent University is offering a Doctoral Research Assistant position in Energy-Efficient Foundation Models. The role combines ML research with a doctoral dissertation and teaching bachelor-level CS courses in Dutch. The two-year initial contract with possible renewals requires a master’s degree in engineering, CS or equivalent, and skills in Python, C++, Java.
Funding follows the AAP3 salary scale. Applicants should be prepared for rigorous research, supervision by IDLab, and collaboration within
Apply by 17 Nov 2026
About This Opportunity
Ghent University advertises Doctoral Research Assistant – Energy-Efficient Foundation Models (Ghent), focusing on machine learning for energy-efficient foundation models.
Ghent University IDLab advertises this research assistant position in the Faculty of Engineering and Architecture, with at least 50% of working time devoted to a doctoral dissertation developing energy-efficient foundation models. It also includes bachelor-level computer-science teaching in Dutch and departmental academic service. A relevant engineering or computer-science master’s degree is required and candidates with non-EU qualifications may need a NARIC equivalence certificate. Programming skills in Python, C++, C# or Java are assets. Salary follows the AAP3 scale. The initial contract lasts two years with up to two renewals after positive assessments. This is the machine-learning vacancy referenced 30464, rather than the separate autonomous-robot-collaboration post. Academic preparation and entry profile: A master’s degree in engineering, engineering technology, computer science or an accepted equivalent; Dutch proficiency sufficient to teach undergraduate courses is mandatory. Funding and appointment conditions: Salary scale AAP3; salary amount not specified. Who This Opportunity Is Best Suited For: Based on the documented project scope, this opportunity may be particularly suited to applicants whose preparation includes A master’s degree in engineering, engineering technology, computer science or an accepted equivalent; Dutch proficiency sufficient to teach undergraduate courses is mandatory; researchers interested in working with Machine learning, Foundation models, Python, C++, Java. This is an editorial fit assessment, not an admissions determination. Potential Challenges / Who May Find It Less Suitable: Relevant considerations are the specialized technical breadth may require significant preparation; teaching commitments may affect how research time is organized. The exact implications depend on the stated eligibility and appointment terms. Overall Opportunity Assessment: The distinctive focus is machine learning for energy-efficient foundation models. Applicants should weigh the verified research methods, qualifications and any stated funding or mobility conditions against their research goals.
Machine learning for energy-efficient foundation models
Level PhD
Field Machine learning for energy-efficient foundation models
Organization Type University
Funding & Compensation
Amount Paid
Funding Type Salary
Funding Status Paid
Education
A master’s degree in engineering, engineering technology, computer science or an accepted equivalent; Dutch proficiency sufficient to teach undergraduate courses is mandatory.