Doctoral fellow

ABOUT GHENT UNIVERSITY

Ghent University is a world of its own. Employing more than 15,000 people, it is actively involved in education and research, management and administration, as well as technical and social service provision on a daily basis. It is one of the largest and most exciting employers in the region and offers excellent career opportunities.
With its 11 faculties and more than 85 departments offering research-based study programmes across a broad range of disciplines, Ghent University is a logical choice for staff and students alike.

YOUR TASKS

We are hiring a full-time PhD researcher within the CVAMO Flanders Make Lab at Ghent University. The project focuses on developing machine learning models to predict manufacturability and manufacturing effort directly from CAD geometry.
The research aims to translate geometric design information into quantitative estimates of manufacturing effort and cost. Methods include Graph Neural Networks, geometric deep learning, and multi-view learning architectures. A strong emphasis is placed on explainable AI to identify which geometric features drive cost increases or infeasibility, thereby providing interpretable managerial decision support.
You will contribute to teaching activities in the department (Data Mining, Machine Learning), up to a maximum of 10% of your appointment.
You may also contribute to the execution of collaborative industry projects, up to a maximum of 10% of your appointment.
You will enroll as a full-time PhD student for four years (upon yearly positive evaluations) in the Department of Management, Innovation and Organisation (Faculty of Economics and Business Administration) under supervision of Prof. Dries Benoit. The successful completion of the project will lead to obtaining a doctoral degree (PhD).

WHAT WE ARE LOOKING FOR

• For this position, we are looking for someone with the following characteristics and assets:
• You hold a Master’s degree (MA or MSc), or are about to complete one in 2026, in a relevant field (e.g., business engineering, industrial engineering, mathematics, engineering, computer science, artificial intelligence). Strong study results are an asset. 
• A strong interest in scientific research in machine learning and AI, preferably with background knowledge in neural networks and deep learning. 
• Strong analytical and programming skills. 
• Clear scientific and communicative skills (critical thinking, scientific writing, presentation skills). 
• A profound knowledge of English is required. 
• Ability to work independently while contributing to a collaborative research environment.

WHAT WE CAN OFFER YOU

• A full-time position as a doctoral fellow, consisting of an initial period of 12 months which, after positive evaluation, will be extended to a maximum of 48 months. 
• Targeted starting date: September 1, 2026. 
• The fellowship amount is 100% of the net salary of an AAP member in equal family circumstances. The individual fellowship amount is determined by Team Personnel Administration based on family status and seniority. A grant that meets the conditions and criteria of the regulations for doctoral fellowships is considered free of personal income tax. Click here for more in-formation about our salary scales 
• Opportunities for conference participation, doctoral school training, and international publication. 
• A stimulating research environment within CVAMO and Flanders Make, closely connected to industrial applications. 
• All Ghent University staff members enjoy various benefits, including training opportunities, holiday leave, bicycle allowance and eco vouchers.

INTERESTED?

Interested? Please apply before April 5, 2026 23:59 via email to dries.benoit@ugent.be: 

• Motivation letter 
• Detailed CV, including study results 
• Copy of your degree and transcripts 

All documents should be in pdf format 

Make sure the subject line of your email starts with “PHD26” 

Ghent University maintains an equal opportunities and diversity policy. Everyone is encouraged to apply. 

More information: 

Prof. Dries Benoit (dries.benoit@ugent.be)