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Ghent University

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PhD Doctoral Fellow in Micro-CT Reconstruction with Machine Learning and Implicit Neural Representations Ghent University in Belgium

Degree Level

PhD

Field of study

Computer Science

Funding

Full-time doctoral fellow position for an initial 12 months, extendable after positive evaluation to a maximum total of 48 months. Fellowship amount is 100% of the net salary of an AAP member in equal family circumstances; the grant is considered free of personal income tax if it meets doctoral fellowship regulations.

Deadline

Dec 18, 2026

Country flag

Country

Belgium

University

Ghent University

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Keywords

Computer Science
Biomedical Engineering
Signal Processing
Electrical Engineering
Medical Imaging
Mathematics
Image Processing
Linear Algebra
Computational Imaging
Inverse Problem
Physics
ML

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About this position

Ghent University is advertising a PhD-level doctoral fellow position in micro-CT reconstruction using machine learning and implicit neural representations (INRs).

The project sits at the intersection of linear algebra, inverse problems, signal processing, computational imaging, and applied AI. The work is connected to the Image Processing and Interpretation (IPI) research group at Ghent University and the Radiation Physics group at the Center for X-ray Tomography (UGCT), with additional collaboration with Centrum Wiskunde en Informatica (CWI) in Amsterdam.

Research tasks include designing, implementing, and validating novel reconstruction algorithms, benchmarking them against state-of-the-art pipelines, and working on mathematically grounded, computation-efficient methods for dynamic imaging and tomography. Strong programming skills in Python/C++, GPU-based computing, and modern machine learning frameworks are required.

Eligibility: a Master's degree in Engineering, Physics, Mathematics, Computer Science, or an equivalent field is preferred and must be completed by the appointment date. Strong interest in signal processing, inverse problems, and mathematics is essential; experience with medical image reconstruction or computational imaging is highly desirable.

Funding: full-time doctoral fellow appointment, initially 12 months and extendable up to 48 months after positive evaluation. The fellowship is set at 100% of the net salary of an AAP member in equal family circumstances and is tax-free if it meets the doctoral fellowship regulations.

Application deadline: 2026-12-18 23:59. Apply by email with a CV, diploma copy (if available), and motivation letter to [email protected].

Funding details

Full-time doctoral fellow position for an initial 12 months, extendable after positive evaluation to a maximum total of 48 months. Fellowship amount is 100% of the net salary of an AAP member in equal family circumstances; the grant is considered free of personal income tax if it meets doctoral fellowship regulations.

What's required

Applicants should hold a Master's degree, preferably in Engineering, Physics, Mathematics, Computer Science, or an equivalent degree, by the date of appointment. Strong interest in signal processing, inverse problems, mathematics, and machine learning is essential. Familiarity with (medical) image reconstruction, tomography, or computational imaging is highly desirable. Strong programming skills in Python/C++ and GPU-based computing, plus proficiency with modern machine learning frameworks, are required. Candidates should be motivated to present at international conferences and contribute critically to state-of-the-art research.

How to apply

Send your CV, a copy of your diploma if available, and a motivation letter to [email protected]. Late applications are not accepted. For questions, contact prof. Jan Aelterman by email.

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