Le laboratoire de l’ancien membre du RBIQ, Maxime Chamberland, recrute un doctorant pour travailler sur les méthodes de visualisation scientifique pour la neuroimagerie.
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Description du poste
We are looking for a motivated PhD candidate that wants to develop exciting scientific visualization methods for Neuroimaging, with a high number of inter-disciplinary aspects interfacing Computer Science and Medical Image analysis. The candidate will help build state-of-the-art open source applications to advance the visualization of complex, multi-dimensional data for improved analysis of MRI data at the individual level.
Medical visualization is an important research subject for the field of personalized-medicine.
In recent years, tremendous progress was made in non-invasive quantitative characterization of brain tissue microstructure using a special technique called diffusion MRI (dMRI). With dMRI, it is possible to reconstruct the complete 3D architecture of the human brain via streamline tractography and therefore gain insight about white matter connectivity. However, fiber tractography produces dense datasets formed of multiple interdigitating three-dimensional lines which makes interaction and direct visualization challenging. Even though dMRI visualization has evolved considerably in the last two decades, the ever-increasing size and dimensionality of the data requires novel tools that integrate statistical analysis and data visualization. Effective visualization of tractography data has the potential to improve diagnosis and computer-aided surgical planning (e.g., for brain tumor resection and epilepsy surgery).
In this project, the candidate will work on the development of computational algorithms and 3D rendering tools that go beyond what is currently available, with the main goal of providing interactive tools for navigating the brain’s circuitry. The candidate will work on exciting topics such as along tract-profiling quantification & visualization, neural rendering, real-time tractography, interactive virtual tract dissection, anomaly detection, feature extraction and dimensionality reduction via machine learning.
It is expected that the candidate will author high-quality scientific papers and showcase outputs of this work at international conferences.
The project will be developed within the visualization cluster under the supervision of Dr. Maxime Chamberland and Prof. Anna Vilanova. Opportunities for externships with international collaborators are also possible.
The visualization cluster (https://research.tue.nl/en/organisations/visualization) at TU/e has a strong track record in visualization and visual analytics for ML models and high-dimensional data. It has generated several award winning contributions at major visualization conferences (IEEE VIS, IEEE InfoVis, IEEE VAST, EuroVis); several successful start-up companies (MagnaView, Process Gold and SynerScope); and a number of techniques that are used on a large scale world-wide.
We are looking for a candidate who meets the following requirements:
- You are enthusiastic about research in scientific data visualization, medical image analysis, 3D render, computer graphics and machine learning.
- You have experience with or a strong background in medical visualization, computer graphics, medical image analysis and/or machine learning. Preferably you finished a master in Computer Science, (Applied) Mathematics, Biomedical Engineering/Imaging.
- Expertise in the field of diffusion magnetic resonance imaging (dMRI) is a plus but not mandatory.
- You have good communication skills and are able to work in a multidisciplinary team.
- You have strong programming skills (e.g., C++, Python, modern OpenGL or VTK).
- You are creative, critical, analytical, motivated and persistent.
- You have a good command of the English language (knowledge of Dutch is not required).
Conditions of employment
A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
- Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
- Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale 27 (min. €.2,541 max. €3,247).
- A year-end bonus of 8.3% and annual vacation pay of 8%.
- High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
- An excellent technical infrastructure, on-campus children’s day care and sports facilities.
- An allowance for commuting, working from home and internet costs.
- A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.
Information and application
Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.
Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.
Do you recognize yourself in this profile and would you like to know more?
Please contact Prof. Anna Vilanova a.vilanova[at]tue.nl.
Are you inspired and would like to know more about working at TU/e? Please visit our career page.
We invite you to submit a complete application by using the apply button.
The application should include a:
- Cover letter in which you describe your motivation and qualifications for the position.
- Curriculum vitae, including a list of your publications and the contact information of three references.
We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.