Research Engineer in Computer Science
il y a 2 jours
**Where**:Institute of Molecular Chemistry, University of Burgundy (ICMUB), Dijon, France
**Specific unit**:Functional and Molecular Imaging, Medical Image Processing (IFTIM), Dijon, France
**Start of the position**:January 2025 - February 2025 (1-year contract)
**Team**:Jean-Louis Alberini, MD, PhD; Olivier Chevallier, MD, PhD; Fabrice Meriaudeau, PhD; Romain Popoff, PhD; Benoît Presles, PhD; Jean-Marc Vrigneaud, PhD
**Project description**
Liver cancer is the sixth most common cancer in the world, but is the second most common cause of cancer death in men and the sixth leading cause of cancer death in women. Among the various types of liver cancer, hepatocellular carcinoma (HCC) can be treated with selective internal radiation therapy (SIRT), which consists in injecting selectively into the hepatic arteries microspheres labelled with yttrium-90 (Y90), a β- emitter. Before Y90 bead injection, several examinations must be performed. First, a hepatic angiography is acquired to identify extrahepatic vessels that must be prophylactically embolised to preserve healthy organs, and a baseline contrast-enhanced magnetic resonance imaging (ceMRI) scan is acquired to visualise the tumour. Then, a simulation of the treatment is performed by injecting macroaggregated albumin labelled with technetium-99m (Tc99m-MAA) as a surrogate for the Y90 particles. A pre-treatment dosimetry is performed by acquiring a single-photon emission computed tomography (SPECT)/computed tomography (CT) scan, which allows to obtain the distribution of Tc99m-MAA and to calculate the Y90 activity to prescribe. Current clinical practice suffers from **two main weaknesses**, one related to the **definition of volumes that are currently segmented manually either on the baseline ceMRI or on the SPECT/CT, which is inconsistent, time-consuming, and is prone to intra
- and inter-operator variabilities **and another related to the **clinical dosimetric models that assume that Y90 microspheres distribute homogeneously, which is not the case. **Two PhD students have already worked on these topics (Félix Quinton and Tien-Phong Pham) and have developed new methods to improve these two weaknesses. Félix has developed ML/DL/AI algorithms to automatically segment the different volumes and Tien-Phong has developed voxel-based dosimetry methods. **The research engineer will be responsible for creating a user-friendly software that makes the various tools / methods developed by these two PhD students easy to use for the clinical team. He will also be responsible for making the software open source. In addition, he will have to improve, optimise and debug the various methods. **He will be based at IFTIM in the ICMUB laboratory and will work in close collaboration with the medical teams of the University Hospital and the Georges François Leclerc Centre, both located in Dijon, Burgundy, France.
**Person specification**
- The mathematical foundations of computer vision (geometry, convolution, optimisation, etc.);
- ML/DL/AI algorithms;
- The principles of continuous integration (CI) and continuous deployment (CD), and theirintegration with Git;
- The Python programming language, the Pytorch library, and some knowledge of C/C++;
- English (at least C1 level).
Status: Cadre
Pay: 2,500.00€ per month
**Education**:
- Master's (required)
Work Location: Hybrid remote in 21000 Dijon
Application Deadline: 31/01/2025
Expected Start Date: 01/02/2025
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