Job Erasmus MC - Ph.D. student

We have one open Ph.D. position in the field of medical image analysis, applied to utilization of pre-operative images in image guided liver interventions. The main objective is to integrate information on the target anatomy as obtained from pre-operative CT(A) or MR images into 3D ultrasound guided interventions. You will develop and evaluate methods to register the pre-operative imaging information to the interventional scene, using the interventional images and (a priori) knowledge on patient motion/deformation.

The Ph.D. position is part of an STW-funded research project, called “4D ultrasound for improved image guidance in minimally invasive needle interventions: the interventional cockpit”. This is a large project of TU Delft (Industrial Design), Erasmus MC (Department of Radiology and BIGR), and Philips Healthcare, and aims at developing optimal ultrasound-guided interventions.

Candidates must have a Master’s degree in physics, electrical/mechanical/biomedical engineering, mathematics, computer science, or a related field. Experience with programming is an advantage. You should be able to work in a multi-disciplinary team. Strong theoretical skills and affinity with experimental work are required.

Our institute is internationally at the forefront of biomedical imaging, and offers a dynamic, challenging, and cooperative research environment. As a Ph.D. student you will get a temporary position of four years (full-time). The gross monthly salary amounts to € 2.086,- in the first year and increases to € 2.673,- in the final year.

Erasmus MC is an internationally recognized center for high-quality, compassionate care, highly rated transfer of knowledge and high-quality knowledge development in the fields of illness and health.

The Biomedical Imaging Group Rotterdam (BIGR; http://www.bigr.nl) of the Departments of Medical Informatics and Radiology of the Erasmus MC, performs innovative fundamental and applied research to develop and validate advanced techniques for the processing and analysis of large, complex, and heterogeneous medical and biological image data sets.

Requests for information should be directed to Theo van Walsum at vacancies@bigr.nl.