Development of Advanced Techniques for Emergency Robotic Catheterization

KU LEUVEN; Belgique; Sur place; EUR 30 000 - 42 000; Plein temps

Avantages offerts par ce poste

Fully-funded PhD position

Teaching assistant opportunities (up 十

Résumé du poste

KU Leuven offers a fully-funded PhD position in the Department of Mechanical Engineering, Faculty of Engineering Technology, Leuven, Belgium. The project focuses on robotic catheterization systems for emergency interventions, combining sensing, control, and instrument coordination.

The role requires a Master’s degree with distinction and strong problem-solving skills, with opportunities for teaching assistance and international collaboration.

Qualifications

• Master’s degree in engineering or computer science with distinction (cum laude) or equivalent excellent academic results.
• Fields may include mechatronics, robotics, control engineering, mechanical engineering, deep learning, medical imaging.
• Admission requirements for KU Leuven Arenberg Doctoral School should be met.
• Candidates should be highly motivated, a team player, and capable of critical independent work.

Connaissances

Team player

Problem-solving

Independent working

Formation

Master’s degree in engineering or computer science

Description du poste

Computer science Computer systems

Computer science Cybernetics

Computer science Modelling tools

Computer science Programming

Computer science Autonomic computing

Organisation/Company KU LEUVEN Department Engineering Technology Research Field Engineering Mechanical engineering Engineering Electrical engineering Engineering Computer engineering Engineering Biomedical engineering Engineering Precision engineering Engineering Project engineering Engineering Systems engineering Computer science Computer architecture Computer science Computer systems Computer science Cybernetics Computer science Modelling tools Computer science Programming Computer science Systems design Computer science Autonomic computing Researcher Profile First Stage Researcher (R1) Application Deadline 30 Oct 2026 - 23:59 (UTC) Country Belgium Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Nov 2026 Is the job funded through the EU Research Framework Programme? Horizon Europe - EIC Reference Number BAP-2026-584 Marie Curie Grant Agreement Number 101291374 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

An increasing number of medical interventions are performed using catheter-based techniques, offering major benefits to patients, including shorter hospital stays, reduced invasiveness, and fewer surgical scars. However, these procedures often rely on fluoroscopic X-ray imaging, exposing clinicians to ionizing radiation during prolonged interventions. To reduce this occupational exposure, clinicians typically wear heavy lead aprons, which can impose a substantial ergonomic burden and contribute to long‑term musculoskeletal problems. Moreover, fluoroscopic imaging provides limited three-dimensional information, making the navigation of complex vascular anatomy challenging. These limitations have stimulated the development of robotic catheterization systems that allow clinicians to operate from a distance, outside the main X-ray field. Yet, current robotic solutions are not sufficiently optimized for time‑critical and highly complex emergency procedures, such as mechanical thrombectomy for acute stroke. Mechanical thrombectomy requires exceptional expertise to navigate multiple guidewires and catheters through intricate vascular anatomy in a coordinated, precise, and atraumatic manner. This PhD will develop advanced robotic catheterization technologies, integrating novel sensing, control, and instrument coordination strategies. The research will focus on enabling fast, safe, and reliable navigation of multiple instruments under the demanding constraints of emergency intervention. Ultimately, the project aims to establish a new generation of robotic catheterization systems that reduce radiation and operator burden while improving the safety, reliability, and accessibility of complex life‑saving interventions.

We are seeking highly motivated and result-oriented candidates which :

• hold a Master’s degree in engineering or computer science, obtained with distinction (cum laude) or equivalent excellent academic results, in a relevant field such as mechatronics, robotics, control engineering, mechanical engineering, deep learning, medical imaging, or a related discipline. The degree and academic record should meet the admission requirements for the PhD programme at the KU Leuven Arenberg Doctoral School;
• are ambitious and driven, while being, above all, an effective team player;
• have demonstrated strong practical problem‑solving skills;
• are highly motivated, capable of working independently, and able to think critically.

The Department of Mechanical Engineering, Faculty of Engineering Technology at the University of Leuven (KU Leuven) is pleased to offer:

• a fully‑funded PhD position (typically a PhD is 4 years);
• exposure to academic tasks through teaching assistant (capped to 10% of the working hours);
• embedding in a highly international state‑of‑the‑art research environment in a dynamic team with an emphasis towards valorization and clinical validation;
• involvement/link to EiC PROMPT project.

Note that the PhD salary in Belgium is similar or higher than the salary of a starting engineer in industry.

The Department of Mechanical Engineering, Faculty of Engineering Technology at the University of Leuven (KU Leuven) is pleased to offer:

• a fully‑funded PhD position (typically a PhD is 4 years);
• exposure to academic tasks through teaching assistant (capped to 10% of the working hours);
• embedding in a highly international state‑of‑the‑art research environment in a dynamic team with an emphasis towards valorization and clinical validation;
• involvement/link to EiC PROMPT project.

Note that the PhD salary in Belgium is similar or higher than the salary of a starting engineer in industry.

Eligibility criteria

We are seeking highly motivated and result-oriented candidates which :

• hold a Master’s degree in engineering or computer science, obtained with distinction (cum laude) or equivalent excellent academic results, in a relevant field such as mechatronics, robotics, control engineering, mechanical engineering, deep learning, medical imaging, or a related discipline. The degree and academic record should meet the admission requirements for the PhD programme at the KU Leuven Arenberg Doctoral School;
• are ambitious and driven, while being, above all, an effective team player;
• have demonstrated strong practical problem‑solving skills;
• are highly motivated, capable of working independently, and able to think critically.