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/CT imaging Description of the topic As this is an interdisciplinary "AI and medicine" project, co-supervision by a doctor and a statistical/machine-learning researcher is planned (iBV / Inria) 1
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: 305,000 euros total funding over the project duration, including: • 199,000 euros for contractual collaborators (PhD students, postdocs, research assistants) • 106,000 euros for operational expenses
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-supervision by a doctor and a statistical/machine-learning researcher is planned (iBV / Inria) 1- Context and Objective: Monitoring tumor response using clinical imaging, such as CT or FDG-PET, has become a
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. Contact Information: Mariángeles KOVACS-AREVALO (postdoc): mariangeles.kovacs-arevalo@pasteur.fr
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-phenotyping of individuals with autism and controls including brain imaging (EEG and MRI) and a battery of cognitive tests. Our group is currently developing new methods for analyzing whole genome and brain
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techniques have been developed to overcome this drawback. Among them we focus on fluctuation of fluorescent molecules methods as they don’t need any specific materiel or fluorophore. The super-resolved image
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reconstructing the super-resolved image is formalized as an inverse problem which is regularized by introducing suitable sparsity constraint. In our team, we have recently proposed both model-based and data-driven
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to meet them: scale-up + GMP production of organoids and tumoroids - Design of the optimized functional prototype - Incorporation of microbead counting and transfer functions - Validation and qualification
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English Candidates with experience in cell culture are encouraged to apply. Experience with imaging, molecular biology, hydrogels, chemistry, microfabrication and microfluidics are highly desirable
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genetics, genomics, imaging processes, computational biology and biochemistry. Our goal is the deep and detailed understanding of fundamental mechanisms in plant biology that may then also be used to develop