FLI
In this section, you will find internships, thesis, post-doctorates, fixed-term and permanent contract vacancies in the network’s partner laboratories.
Liste des annonces
2020/11/03 – Post doc position – PANomic Atlas for non-small CEll lung cancer managEment
OBJECTIVE
The goal of this project is to develop a panomic atlas for lung cancer patients based on clinical data, histological biomarkers and radiomic features extracted from PET/CT images.
MEDICAL CONTEXT AND HYPOTHESIS
In oncology, the main challenge for physicians is to identify the right treatment for the right patient at the right time. This is especially the case for advanced lung cancer, where the identification of biomarkers predictive of treatment response is essential to optimize management. In practice, physicians integrate different types of information into their decisions, mainly from clinical, biological, histological and medical imaging data. Medical imaging, both morphological and functional, is today an essential component in patient management, for diagnosis, therapeutic evaluation and follow-up. However, although medical images are systematically acquired during the patient's care, they remain largely under-exploited today. The assumption that medical images contain much more information than is currently extracted has led to the development of a new discipline, Radiomics, which has grown rapidly since 2010 (more than 2500 publications using the term "radiomics" according to PubMed).
Given the complexity and wide variety of data available to physicians, we assume that machine learning approaches can assist in the identification of a small group of patients with very similar characteristics, in a reference database, consisting of patients already treated for the same pathology. The medical history of these "twins" will allow doctors to access valuable information to identify the therapeutic strategy to be adopted for the new subject.
CHALLENGES AND POTENTIAL METHODOLOGICAL INVESTIGATIONS.
All methodological developments will be performed by LITO in close collaboration with the Departments of Nuclear Medicine, Radiology ad Medical Oncology of Institut Curie. The database to be used will include about 400 cases from Institut Curie. The challenges to be tackled include:
- Designing a tool for navigating through an extensive atlas for lung cancer lesions.
- Defining new radiomic features to be integrated into the atlas patient profile in order to fully exploit the potential of whole-body imaging.
- Developing methods to correct for multicentric variability that affects radiomic feature values.
- Identifying biomarkers predictive of response to treatment or prognosis among the characteristics available in the patient profile and to evaluate the contributions of each type of information (clinical, histological, biological, imaging).
- Demonstrating the relevance of the approach to patient management in relation to current practices.
References:
1. Orlhac F, Cassou-Mounat T, Pierga J-Y, Luporsi M, Nioche C, Bouveyron C, Ayache N, Jehanno N, Livartowski A, Buvat I. Can we identify « twin patients to predict response to neoadjuvant chemotherapy in breast cancer? J Nucl Med. 61:275, 2020. 2. Orlhac F, Boughdad S, Philippe C, Stalla-Bourdillon H, Nioche C, Champion L, Soussan M, Frouin F, Frouin V, Buvat I. A post-reconstruction harmonization method for multicenter radiomic studies in PET. J Nucl Med. 59:1321–1328, 2018.
3. Nioche C, Orlhac F, Boughdad S, Reuzé S, Goya-Outi J, Robert C, Pellot-Barakat C, Soussan M, Frouin F, Buvat I. LIFEx: a freeware for radiomic feature calculation in multimodality imaging to accelerate advances in the characterization of tumor heterogeneity. Cancer Res. 78:4786– 4789, 2018.
2020/10/16 – Thèse : l’imagerie multimodale des interactions neurogliales
CONTEXTE SCIENTIFIQUE
Les besoins thérapeutiques liées aux maladies du système nerveux central ne sont que partiellement couverts par les médicaments actuels. Il est nécessaire de revisiter certains concepts pharmacologiques afin d’ouvrir le champ à de nouvelles stratégies thérapeutiques, notamment en ciblant des cellules autres que les neurones. Ainsi, les cellules gliales, qui composant 50% des cellules cérébrales de l’Homme, sont dorénavant considérées comme des acteurs à part entière dans la transmission des signaux chimiques et la régulation des neurones. Parmi les cellules gliales, les astrocytes contribuent à cette ‘gliotransmission’ et leurs connexines sont proposées comme une cible pour améliorer le profil pharmacologique de médicaments utilisés en neurologie et psychiatrie. Si la gliopharmacologie (par analogie à la neuropharmacologie) est un nouvel enjeu pour les médicaments de demain en neuropsychiatrie, il est primordial d’avoir à disposition des approches in vivo permettant leurs explorations. Dans ce contexte, la neuroimagerie TEP et IRM offre un champ d’exploration à la fois moléculaire et fonctionnel, tout en étant translationnel, de l’animal à l’Homme.
PROJET DE THESE
La thèse aura pour but de montrer que la neuroimagerie TEP, IRM et par ultrasons à haute résolution (fUS) permet l’exploration des réseaux neurogliaux afin de comprendre leurs contributions moléculaires, cellulaires et fonctionnelles au décours de processus pharmacologiques.
Ses objectifs seront les suivants :
1. Identifier les contributions respectives des neurones et des principales cellules gliales (les astrocytes) dans les données d’imagerie multimodale (TEP, IRMf et fUS) obtenues sur des modèles animaux
2. Explorer par neuroimagerie l’impact de modulateurs pharmacologiques – et notamment de médicaments à visée cérébrale – sur ces diverses populations cellulaires du cerveau.
3. Développer et valider un outil préclinique inédit de neuroimagerie multimodale contribuant à l’obtention de données expérimentales pour la gliopharmacologie.
2020/10/16 – Post doctorant.e – Nouvelles sondes IRM reposant sur un procédé innovant de fabrication additive
Post-doctoral Fellow position for developing new family of MRI probe based on innovative additive manufacturing process.
A 2-years postdoctoral fellow position is available at the University Claude Bernard Lyon 1, Villeurbanne France. The postdoctoral fellow will participate in a multi-disciplinary research program that develops novel MRI coils dedicated to tissue engineering 3D characterizationi. The postdoctoral fellow will work as part of different research groups ( AMPERE, 3DFAB and LGEF) as well as a group of graduate students, postdoctoral fellows, faculty and scientists in the AMPERE lab as many of the work will be developed on its “plastronic” platform.
Primary research area focus
1) Integrating monitoring devices for in vivo imaging of engineered tissue constructs: heating and gas administration systems, optical physiological sensor, smartly Interfacing RF coil and peripherals to control devices. Designing dedicated MRI coil for in vivo imaging could be necessary.
2) Imaging with one multifunctional “MRI probe”: coil characterization by imaging and comparison with measurements on bench. After validation of the MRI probe, the design will be replicated to be tested by non-expert on different platforms of the French network of in-vivo imaging.
Responsabilities
All applicants will be expected to utilize and extend state-of-the-art MRI instrumentation to developed new tools to facilitate imaging of biological constructs in vivo. Specifically, the main tasks will involve coil design/fabrication, integration of peripherals such as piezo-actuators for magnetic resonance elastography, data collection, management and analysis, image post-processing, multi-parametric cohort analysis.
2020/09/15 – Post doctorant.e IRM à ultra haut champ magnétique
Motion correction for brain Magnetic Resonance Imaging at high and ultra-high field.
We are looking for a curious, motivated, team-oriented candidate with a PhD degree in signal processing, physics, computer science, applied mathematics, biomedical engineering or related topics. Prior knowledge in magnetic resonance parallel imaging acquisition and reconstruction techniques would be advantageous.
The successful candidate will work in the central nervous system team composed of physicists, neuroscientists, clinicians and computational scientists.
Salary is based on previous experience (2.7-3.2 k€ monthly gross salary).
The position is granted by Aix Marseille University (www.univ-amu.fr) in a partnership project with
Siemens Healthineers. The work will be done at the CRMBM laboratory (www.crmbm.univ-amu.fr) which is located in the center of the lively Marseille city, within La Timone university hospital.
2020/09/15 – Ingénieur.e biomédical.e en imagerie médicale
Dans le cadre d’un projet d’Innovation Technologique porté par Stéphane Mornet (ICMCB - Institut de Chimie de la Matière Condensée de Bordeaux), l’Université de Bordeaux recrute un ingénieur(e) biomédical (spécialité imagerie médicale) pour un contrat à durée déterminée (un an minimum avec prolongement éventuel). Le/la candidat(e) sera impliqué dans un programme de R&D dédié à la maturation (preuve de concept, validation in vivo, optimisation) de nanoparticules diagnostiques innovantes. Il/elle travaillera dans un environnement interdisciplinaire à l’interface entre chimie, imagerie biomédicale et problématiques médicales.
Le travail expérimental sera réalisé sur une plateforme d’imagerie biomédicale (IRM pré-clinique et clinique, imagerie optique) située sur le campus Carreire de l’université de Bordeaux.
Missions :
1- Effectuer des mesures de relaxométrie RMN sur les nanoparticules (acquisitions, analyse des résultats et rédaction de comptes rendus)
2- Réaliser les acquisitions IRM pré-cliniques sur modèles animaux (souris)
- Mise en place des protocoles IRM
- Acquisitions des images in vivo
- Analyses qualitatives et quantitatives des résultats IRM
- Réalisation de profils pharmacocinétiques et analyses de biodistribution
- Rédaction de comptes rendus et de synthèses sur le déroulement et les résultats de l’étude IRM in vivo
3- Contribuer à l’intégration des résultats IRM avec ceux obtenues in vivo par imagerie de fluorescence et ex vivo sur prélèvement et par histologie.
2020/06/17 – Doctorat “Positron Emission Tomography Image Reconstruction”
Context and objectives.
Nuclear imaging, especially positron emission tomography (PET), is a powerful tool of nuclear medicine in oncology. The development of multimodality (PET-CT, PET-MR) along with advances in PET technology enable ever-increasing precision and accuracy in the quantification of molecular processes in vivo. However, PET measurements do not directly lead to images and a complex inverse tomographic problem has _first to be solved. This task of tomographic reconstruction is essential in PET as it may have a significant impact on image quantification, and thus the outcome. In this context, this PhD project focus on the development of innovative tomographic image reconstruction methods in order to tackle current and future challenges raised by applications where the recorded signal is weak.
Our team has a recognized expertise in 90Y PET imaging for postinfusion quantitative assessment following radioembolization therapy in liver cancer [1]. The challenge of this application is to be able to evaluate the delivered dose inside and outside the targeted lesions, from the reconstruction of the
90Y PET signal [2]. This signal is characterized by very few interesting events hidden in a high level of background events [3, 4], making the tomographic reconstruction problem very ill-posed. From current state-of-the-art methods, reconstructed images su_er from high levels of noise and local bias, which do not allow for precise dosimetry.
In the continuation of the efforts lead by the team, the candidate will work on the development and evaluation of methods adapted to this challenging application. The PhD project has two main objectives.
The first objective is to build innovative PET reconstruction algorithms allowing to further optimize the compromise between bias and noise, as compared to currently investigated algorithms. These algorithms could be driven by the flexible -divergence [5] and include a penalty term based on the recently proposed deep image prior [6]. The second objective is to develop a method able to associate confidence values on dosimetry measurements extracted from the reconstructed PET images. As PET images intrinsically suffer from inaccuracy and/or imprecision, being able to deliver confidence values or intervals associated to them seems natural but is a challenge. The developments would be based on recently proposed bayesian posterior bootstrap methods [7] that provided promising preliminary results when applied to PET reconstruction.
Current protocols are running on PET/CT scanners. A hybrid PET/MR scanner will be installed in 2021 at the University Hospital. Future patients treated with 90Y will benefit from the use of this scanner for improved liver imaging thanks to MR. The use of MR information in the PET reconstruction process and the estimation of confidence values is of particular interest. Taking advantage of multimodality will be an integrated part of the PhD project.
The position is funded by iemens Healthineers (these Cifre). The collaboration between Siemens Healthineers and the University Hospital is of long duration. The project will also be conducted in partnership with the Numerical Science Laboratory in Ecole Centrale Nantes and will be associated with the work done by a current PhD student.
2020/05/18 – CDD “Technicien Biologie / Biochimie / Biophysique pour l’imagerie préclinique”
Contexte
Le thème central de recherche du laboratoire est l’étude et la reconstruction des tissus orofaciaux. Nos travaux sont axés sur la compréhension des mécanismes liés à la formation et à la régénération de cette sphère en nous basant, d’une part sur l’étude des cellules qui la constituent, et de l’autre sur la matrice extracellulaire qu’elles produisent. Le laboratoire a aussi pour mission la formation en recherche des étudiants de la licence jusqu’au doctorat. Le laboratoire héberge la modalité micro-CT pour l'imagerie préclinique de la plateforme d’imagerie du vivant (PIV) de l’Université de Paris.
Issue du rapprochement des Universités Paris Descartes et Paris Diderot et intégrant l’Institut de physique du globe de Paris, l’Université de PARIS propose pour la première fois sur le territoire parisien, une offre de formation pluridisciplinaire des plus complètes et des plus ambitieuses en recherche, tout en ayant un fort rayonnement international.
Mission
L’agent devra assurer les missions suivantes :
· préparer les expérimentations en respectant le protocole préétabli ;
· Acquisitions et traitements des données micro-CT
· Surveiller statuts sanitaires ;
· Appliquer les réglementations du domaine d’étude ;
· Recueillir et mettre en forme les informations nécessaires à la bonne conduite de l’expérimentation ou requises par la législation ;
· Tenir un cahier de laboratoire ;
· Gérer les stocks et les commandes ;
· Assurer l’entretien et la maintenance de premier niveau du matériel et des équipements ;
2020/05/05 – Doctorat “Dosimetric improvements for selective internal radiation therapy of hepatic tumours and impact on patient response”
Liver cancer is the sixth most common cancer in the world but the second leading cause of cancer mortality in men. Among the different types of liver cancer, some can be treated by selective internal radiation therapy (SIRT), which consists in injecting Yttrium-90 (90Y) β-emitter microspheres into the liver. This project aims at improving SIRT treatments by bringing state-of-the-art dosimetric techniques to SIRT that will be validated through Monte-Carlo simulations, and developing deep learning methods to predict treatment response from previous dosimetric models.
The 90Y microspheres injection treatment has multiple steps. An acquisition of magnetic resonance imaging (MRI) is performed, followed by a simulation of the treatment via a technetium-99m macroaggregated albumin (Tc99m-MAA) single-photon emission computed tomography (SPECT)/CT scan. This SPECT/CT scan leads to compute a pre-treatment dosimetry and allows to determine the amount of 90Y microspheres needed for the treatment. Right after the injection of 90Y microspheres, a positron emission tomography (PET)/CT scan is acquired to compute a 90Y-treatment dosimetry. This dosimetry should be as accurate as possible to document the actual dose delivered to the targets in SIRT. Besides, there is increasing evidence of a dose-effect relationship in the case of SIRT. However, dosimetric results are known to be very sensitive to technical factors (acquisition, reconstruction, segmentation, dosimetric models) and, in the absence of standardised techniques, a bunch of dosimetric thresholds has been reported in the literature. Until recently, most of the dosimetry models have been carried out using empiric formulae or simplified dosimetric models.
OBJECTIVES
The first aim of this work is to validate a more accurate dosimetric model for both the Tc99m-MAA-pre-treatment and the 90Y-post-treatment by using a Monte-Carlo approach with the GATE toolkit. This validation implies simulations of physical phantoms representative of the liver uptake in SIRT and comparisons with state-of-the-art techniques such as the voxelized dosimetry used in clinical routine.
Based on the data collected since 2012, the second aim of this work is to develop a supervised deep learning classification approach to predict the treatment response using either the Tc99-MAA-pretreatment dosimetry or the 90Y-treatment dosimetry or both and assess correlations from our validated dosimetric calculations.
2020/02/27 – CDI Ingénieur plateforme big data pour la neuroimagerie
La mise en place au CEA d’une plateforme pour la médecine du futur va nécessiter, non seulement, le développement d’une infrastructure importante au Très Grand Centre de Calcul du CEA (TGCC) pour héberger du stockage et des moyens de calcul, mais également la création d’un portail métier développé à Neurospin pour les besoins propres à l’univers de la neuroimagerie. Ce portail sera principalement composé de services et d’outils logiciels qui serviront d’interface entre les chercheurs du CEA et d’ailleurs et l’infrastructure du TGCC. Il permettra de fluidifier l’analyse des très grandes bases de données comme UK Biobank (100 000 sujets), ou des agrégations complexes de bases de données issues de la plateforme CATI (https://cati-neuroimaging.com/).
Ce poste a pour but de permettre la mise en place, la maintenance et l’évolution de cette plateforme métier afin de répondre aux défis suivants :
- Amener la communauté du big data vers la neuroimagerie, en mettant à disposition de
grands gisements de données annotées et les moyens de calcul adéquats.
- Harmonisation des données et des méta-données. La réutilisation des données et des logiciels par différents chercheurs étant un aspect important de la plateforme, il est indispensable de fournir les outils permettant d’assurer une cohérence entre les organisations des données et des métadonnées des différentes études.
- Gestion des droits. Les bases de données collectées par le CATI n’appartiennent pas au CEA.
Un des objectifs de la plateforme est de créer un cloud mis à disposition des utilisateurs de
chaque base avec des droits sous la responsabilité de chaque promoteur. Ce service nécessite des développements conséquents.
- Développement logiciel et sécurité. Les logiciels de recherche sont en constante évolution. La plateforme métier devra apporter le meilleur compromis entre, d’une part, les chercheurs qui souhaitent pouvoir modifier très librement le cœur des logiciels et, d’autre part, l’utilisation des logiciels dans une plateforme exigeant un haut niveau de sécurité.
2019/12/20 – MRI Application Scientist at Bruker
You will be integrated into our international application team, which will bring you in contact with the leading experts in the field and will require close co-operation with colleagues in the integration, soft- and hardware departments.
The tasks include:
- Demonstration of our preclinical imaging systems, in particular MRI
- Creating protocols, workflows and optimizing application sequences
- Customer training worldwide (with a focus on Europe)
- Customer teaching (in-house, webinars) Sales and after sales support (e.g. customer hotline, customer visits)
- Support of system integration and component specification
- Creation of user documentation and training material Marketing support (marketing materials, lectures, and data preparation) Assist in trade shows and conferences worldwide - -- Working with small rodents