PhD Position Experimental Physics – Advanced Detector Development for Spectral Photon-Counting CT

Develop an ultrafast X-ray photon-counting detector for “color” CT imaging in medical and industrial applications. Contribute to making the next-generation CT more precise, accessible, and affordable. Join our open minded, international and collaborative research team.

Job description
Photon-counting computed tomography (PCCT) represents the next leap in (medical) X-ray CT. It delivers images with astonishing contrast and resolution, while lowering the X-ray dose received by the patient. Moreover, the spectral capabilities of PCCT (also called “color” CT) enable quantitative imaging functions, such as measuring tissue composition or the concentration of contrast agents. Unfortunately, widespread use of PCCT is still limited by the high cost of current X-ray photon-counting detectors.

You will work within the EU-funded QuPIX project, which aims to unlock the full potential of color CT by developing and validating a novel X-ray photon-counting detector based on quantum-enhanced perovskite scintillators and silicon photomultipliers. As a PhD student within the section Medical Physics & Technology (MP&T) at TU Delft, you will design, build, test, and optimise detector prototypes and demonstrate proof-of-concept performance. Your project spans the full experimental chain: prototype design, instrumentation development, experimental characterization, data acquisition, digital signal processing, troubleshooting, and theoretical modelling. During these activities, you will work closely with our technical support staff, such as electrical and mechanical engineers. The focus is on hardware development (not medical image reconstruction or processing).

You will be part of the Medical Physics & Technology section in the Radiation Science & Technology department of the Faculty of Applied Sciences at TU Delft. We value quality in research and education as much as we value an open, safe, and inclusive working environment. Our mission is to develop better technologies for the personalized diagnosis and treatment of disease, focusing on radiation-based approaches in medical imaging, radiation oncology, and image-guided interventions.

Deadline 23 Mar ’26

More information: here