Open PhD position (University of Strasbourg / ICUBE / IRCAD)
Friday 2nd October 2020
Closing Date: Nov. 1st 2020
The research group IMages, leArning, Geometry and Statistics (IMAGES), member of the ICube lab at the University of Strasbourg, are opening a PhD position in collaboration with the IRCAD institute, starting Sept. 2020.
The general framework of the research project is computer assistance to needle insertion for percutaneous surgery, and more particularly thermal ablations of tumors. The objective is to help the interventional radiologist, not only in preparing the intervention preoperatively, but in guiding the insertion intraoperatively as well.
In this PhD, the candidate will first work on several approaches to improve computation times of multi-objective optimization and treatment simulation methods, using GPU, code optimization, or hybrid methods with precomputations reducing parameters or iterations. The second challenge in this thesis will be the intraoperative guidance. Initial work will have to be done on initial registration of the 3D model on the actual patient, the transmission of the position of the tracked tool, and an intuitive visualization and guidance using augmented reality to help correct the trajectory. Finally, approaches for the simulation of deformation, real-time registration, and motion tracking will be considered to allow for the best re-evaluation of the constraints to satisfy at all times by the tool relatively to its current position.
The targeted clinical application will be the percutaneous thermal ablation (RFA or cryo) of abdominal tumors (hepatic, renal, desmoid).
The PhD student will be co-hosted for 3 years in the Surgical Data Science team of IRCAD Strasbourg and the IMAGeS group of ICUBE Strasbourg.
With around 650 members, ICube lab is a major driving force for research in Strasbourg that gathers together researchers from the University of Strasbourg, the French National Center for Scientific Research (CNRS), and the University Hospital. The IMAGeS group is a multinational research group of around 30 members (academic, post-doc, PhDs and graduate students), with a strong track record in biomedical engineering and AI, and more particularly image processing, computer vision, graphics, and computer-assisted surgery. The lab offers a dynamic, challenging, and cooperative research environment, in close collaboration with clinicians from the university hospital.
The IRCAD Surgical Data Science team has been researching and developing augmented surgery software for 20 years that is intended to assist surgeons, interventional radiologists and gastroenterologists. The complexity and multiplicity of challenges associated with augmented surgery naturally require a team of suitable size. Consequently, in addition to its collaborations with the University of Strasbourg, the Surgical Data Science team is developing and forging international partnerships thanks to twin IRCAD institutes, and in particular IRCAD Africa, located in Kigali. The growth of the IRCAD Africa Surgical Data Science team has been carefully planned. The team now has 9 members, reaching 40 members within 5 years. To achieve this ambitious goal, IRCAD Africa is supporting the most deserving African computer scientists to receive funding enabling them to complete their doctoral training in Strasbourg. The best post-graduates also have the opportunity to help lead, mentor and train new talents in IRCAD Africa in a virtuous cycle.
Both institutes are located in Strasbourg, a lively, green and cosmopolitan city, home of the European parliament and located in the heart of Europe, that will host the MICCAI conference in 2021. The PhD candidates will have a unique opportunity to take part in the organization of the event.
Qualification and skills
We are looking for dynamic and motivated candidates with an MSc degree in Computer Science or equivalent. Strong programming skills in C++/python are required. Knowledge and experience with augmented reality, computer graphics, image processing, optimization techniques or related fields as well as advanced machine learning approaches such as deep learning is an advantage. You should be able to work in a multi-disciplinary team, interested in interdisciplinary applied research, and have a good oral and written proficiency in English. Strong theoretical skills and affinity with experimental work are required.
Information and application
Please send a long CV, motivation letter and academic transcripts in English or French with ranking information before Nov 1st, 2020 to Caroline Essert: email@example.com and Alexandre Hostettler: firstname.lastname@example.org
|Organization||University of Strasbourg / ICUBE / IRCAD|
|Title||Open PhD position|