Research Engineer - Medical image quality control tools to assess radiation-induced neurotoxicity

The Centre Inria de l’Université de Grenoble groups together almost 600 people in 22 research teams and 7 research support departments.

Staff is present on three campuses in Grenoble, in close collaboration with other research and higher education institutions (Université Grenoble Alpes, CNRS, CEA, INRAE, …), but also with key economic players in the area.

The Centre Inria de l’Université Grenoble Alpe is active in the fields of high-performance computing, verification and embedded systems, modeling of the environment at multiple levels, and data science and artificial intelligence. The center is a top-level scientific institute with an extensive network of international collaborations in Europe and the rest of the world.

Radiotherapy (RT) is one of the most important treatments of primary brain tumors, of which 60% are high grade. However, its potential neurotoxicity on the central nervous system is a highly relevant clinical issue. It is also part of the priority research questions in radiation protection, regarding the identification and the prevention of non-cancer side effects related to the use of ionizing radiation (IR) for therapeutic purposes. Currently, the most frequent and threatening mid to long-term neurotoxic complication of brain RT is cognitive dysfunction related to radiation-induced leukoencephalopathy (RIL). Image-based biomarkers for RIL include diffuse supratentorial white-matter lesions (WML), ventricular dilatation, and brain atrophy (BA). The associated cognitive impairments can dramatically reduce the quality of life for long-term survivors. The neurocognitive status is also an important end-point in clinical trials. However, the underlying physiopathology of radiation-induced neurotoxicity in normal tissues and organs is poorly understood as well as its potential links with the initiation and temporal progression of specific cognitive dysfunctions.

The candidate will work in the context of the ANR project Radio-Aide, which will offer a stimulating research environment gathering experts in Image processing, Neurosciences & Neuroimaging, in Advanced Statistical and Machine Learning methods with a strong collaboration with neuroradiologists and neuro-oncologists. 

The successful applicant will be involved in several crucial medical imaging processing steps: data quality control and harmonization of multi-centre datasets.

Based on the multimodal data from an ongoing cohort (n=224; 2/3 are already collected), the main objectives  are to develop advanced spatio-temporal models and innovative AI tools for brain MRI data processing to i) generate new knowledge about the underlying neurotoxic mechanisms implied in the initiation and temporal progression of specific cognitive dysfunctions following brain RT and the radioresistance of targeted anatomic and functional structures, accounting for the tumor- response status as essential contextual data and to ii) predict individual cognitive side-effects at early stage after brain RT to set up mitigation measures to preserve the quality of life for survivors.

The applicant should have skills in MR imaging and image analysis. Moreover, Python programming skills is a key prerequisite. The candidate should be fluent in English (and preferably in French which will be the working language), have a good communication skills and organizational skills.

• Subsidized meals
• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
• Possibility of teleworking and flexible organization of working hours
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities
• Access to vocational training
• Social security coverage