Ongeveer 23 uur geleden - Technische Universiteit Eindhoven - Eindhoven
Engineering PhD Student for Q-Maestro: Improving Stroke Treatment by Advanced Analysis of Digital Subtraction Angiography Images
Ischemic stroke is a worldwide major cause of death and permanent disability. Several recent RCTs have shown that patient outcome in acute stroke caused by an …
- 's-Gravendijkwal, Rotterdam, Zuid-Holland
- Tijdelijk contract / Tijdelijke opdracht
- Uren per week:
- 36 - 36 uur
- € 2422 - € 3103 per maand
Ischemic stroke is a worldwide major cause of death and permanent disability. Several recent RCTs have shown that patient outcome in acute stroke caused by an occlusion of a large vessel could be dramatically improved by intra-arterial treatment in which the occluding thrombus is mechanically removed from the occluded vessel. Imaging during these endovascular interventions is highly relevant for therapeutic decision making as it guides the interventionist during the procedure. However, in addition to this anatomical information these images may provide additional information on perfusion of the affected brain tissue. Knowledge on how this perfusion data relates to clinical outcome, and technology to obtain objective quantitative perfusion data from intervention DSA images, however, is currently virtually lacking.
This project therefore aims to develop and assess methods to quantify (microvascular) perfusion in Digital Subtraction Angiography (DSA) images during endovascular treatment for acute ischemic stroke. For this, we are currently looking for two PhD students: one with a clinical background and one with a background in an engineering field. They will co-work on this project: the engineering PhD will work on image processing approaches (traditional and/or AI-based) to extract relevant information from clinical DSA images, whereas the clinical PhD will focus on investigating associations between DSA-derived perfusion parameters and clinical data such as patient outcome and endovascular techniques. This vacancy is for the engineering PhD.
We are looking for highly motivated candidates with a university MSc degree, that want to contribute to the rapidly developing field of stroke treatment. Candidates are expected to have outstanding theoretical and experimental research skills, to be well organized and result-driven, and to have a strong team spirit. Candidates also must have strong English language skills (written and oral).
The candidate should have a degree in an relevant engineering field (Physics, Electrical Engineering, Computer-Science or related field), must have knowledge of medical imaging and machine learning; knowledge of modern AI techniques is an advantage. Also, the engineering PhD candidate should have experience with implementing image analysis methods in a common programming language (C / C++ / python).
ConditionsThe position is available from November 1st, 2019. You will receive a temporary position for 4 years. The gross monthly salary is € 2.422,00 in the 1st year and increases to € 3.103,00 in the 4th year (scale OIO). The terms of employment are according to the Collective Bargaining Agreement for Dutch University Medical Centers (CAO UMC).
Additional informationFor more information about this position, or queries regarding your application, please contact: Dr.ir. Theo van Walsum, e-mail: email@example.com or Dr. Adriaan van Es, e-mail: firstname.lastname@example.org. For queries regarding your application, please contact Jerry Chandansingh, Recruiter, by phone number: +31 (0)6 500 310 06.
If you are excited by the thought of this position and would like to apply, please do so by using the application form on our website, including the following documents: Cover letter (explaining your motivation and suitability for the position); CV/ resume (including your final marks, research projects or internships and relevant courses, copy of your MSc thesis); Names and contact details of at least two references willing to provide a recommendation letter on enquiry.
Selection will be based solely on academic excellence and research potential. Short-listed applicants will be interviewed either in person or via video conference call.