Amsterdam UMC (AMC) – PhD Student on Deformable Biomechanical Transformation Modeling for Image Registration


We are looking for a highly motivated candidate for a fully funded Ph.D. student position at Amsterdam UMC, location Academic Medical Center (AMC)).

Deformable image registration is the process of aligning two images by determining the transformation that maps points in one image to their corresponding points in the other image. Deformable image registration has potentially huge added value to many applications in healthcare since images form a cornerstone for many diagnoses, treatments, and follow-up in modern medicine. Key reasons why clinical implementation has proven to be extremely challenging are lack of robustness, limited success for registration problems involving large deformations or content mismatches, and a lack of insightful tuning possibilities.

In this project, we aim to go beyond the proof-of-concept stage of a novel, multi-objective, approach to deformable image registration for which a pilot implementation was previously made by the Amsterdam UMC, location AMC and Centrum Wiskunde & Informatica (CWI; the Dutch national research institute for mathematics and computer science).

We will focus on the utilization of this approach within a key medical area that stands to benefit from accurate deformable image registration: radiation therapy. With this project we wish to truly bridge the gap between theoretically powerful deformable image registration software and real-world practically (i.e., clinically) useful software tools to realize the true potential of deformable image registration for radiation therapy.

We currently specifically seek a candidate for the subproject that mainly focuses on the design of efficient representations of meshes that can be outfitted with biomechanical properties to serve as the transformation model over which optimization proceeds. Moreover, gradient properties of such meshes need to be derived with respect to the objectives of interest used in the multi-objective optimization. The resulting biomechanical transformation model needs to be able to cope with large deformations (including e.g., sliding tissues) and content mismatches.

This project will ultimately consist of four full-time research positions and a part-time radiation therapy technologist position.


Candidates are required to have an M.Sc. degree in computer science, physics, or similar area with relevant experience, and a research interest in clinical applications. If you are obtaining your M.Sc. degree before September 2019, you are also invited to respond.

It is essential that you have a clear interest in working both on fundamental research as well as on applying this research, in collaboration with academic partners and company partners. We expect a flexible, can-do mentality and attitude with a willingness to cooperate with experts across different disciplines (including computer science, physics, and medicine). Further, you are highly motivated to develop your skills as an independent researcher.

Applicants are required to have substantial programming skills (C/C++ experience is a pre). Applicants are further expected to have an excellent command of English.


This position is available within the project titled “Multi-Objective Deformable Image Registration (MODIR) – An Innovative Synergy of Multi-Objective Optimization, Machine Learning, and Biomechanical Modeling for the Registration of Medical Images with Content Mismatch and Large Deformations”. This project is funded within the Open Technology Programme (OTP) of the Dutch Organization for Scientific Research NWO Domain Applied and Technical Sciences (TTW, formerly Technology Foundation STW) with industrial partners Elekta and Xomnia.

The project is a collaboration between the department of Radiation Oncology of the Amsterdam UMC, location AMC and the Life Sciences and Health research group of the CWI, both located in Amsterdam, the Netherlands.

AMC and CWI closely collaborate on multiple joint projects in which they work on innovations along the entire spectrum from algorithmic foundations to clinical integration. Candidates are expected to spend at least one day per week at the CWI.

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