Open PhD position on deep learning for medical images at UCLouvain, Belgium

The Université catholique de Louvain (UCLouvain) is hiring a PhD student within the framework of a project called "DeepContour" (Deep learning for automatic organ contouring of medical images in adaptive radiation therapy).
The project takes place at the crossing of machine learning and cancer treatment with photon or proton therapy).
To target the tumor and avoid organs at risk, radiation oncology heavily relies on medical images that must be annotated with the contours of these structures.
This difficult task is still performed mainly manually by physicians.
On the other hand, automatic recognition and delineation of organs in medical images is often turned into an image registration problem: a reference image, called atlas and manually segmented by an expert, is non-rigidly deformed to match the image to be segmented.
Registration can however suffer from inaccuracies, especially when trying to match anatomies of different patients.
DeepContour follows a different approach of the atlas, based on machine learning techniques.
Reference images will be used to train classifiers, namely, deep neural networks, which can afterwards process new images and label pixels or homogeneous groups of pixels, called superpixels.
A previous proof-of-concept has demonstrated the validity of this approach and the project aims to improve the methodology by:
* Defining new features to optimise prior segmentation into superpixels and therefore final, accurate delineation of organs (shape and texture features could be used in addition to gray level, distance and contiguity to organs).
* Managing unexpected or unpredictable objects (like medical devices, tumours, etc.), particularly difficult to deal with in image registration.
* Transpose from natural scenes to medical images an architecture that combines deep neural networks and superpixels.
* Make the methodology interactive (ask the user whenever the risk of error is significant) and adaptive (learn from new images segmented by the atlas and approved by physicians).
The project also includes the collection of reference data with a clinical partner and the comparison with registration-based atlases.
The ideal PhD student should have a master degree in engineering, computer science, or applied mathematics.
S/he should have a good background in mathematics, statistics, and programming (Python, Matlab, scripting langages), completed with scientific curiosity and good communication skills.
S/he will work in a multidisciplinary and dynamic environment (engineers, mathematicians, physicists, physicians), sharing its time between the ICTEAM Institute (Information and Communication Technologies, Electronics, and Applied Mathematics, Louvain-la-Neuve) and the IREC (Institut de Recherche Expérimentale et Clinique, Brussels).
S/he should speak at least English or French and be willing to learn the other language.
The contract is a 2+2 scholarship.
Two years are already secured, the 3rd and 4th depend on evaluation after the first two years.
The candidate should be eligible for a Belgian, tax-free PhD scholarship (EU citizen and holder of a Master degree).
The net salary is about 1700-1800 euros/month.
Applications will be considered as they are received; the position will remain open until filled.
The contract is planned to start in October 2016.
The Université catholique de Louvain (http://www.uclouvain.be) is the largest and highest-ranked university in the French-speaking part of Belgium, with more than 28000 students, 3600 researchers, and 2000 PhD students.
It is located mainly in Louvain-la-Neuve (25km in the South-East of Brussels) and the outskirts of Brussels (University hospital and medicine school).
The University provides easy access to language courses, as well as sport facilities and cultural events.
Contact information: john.lee-AT-uclouvain.be (send a CV and motivation letter)