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21 Aug 2025 Job Information Organisation/Company CNRS Department Laboratoire d'analyse et d'architecture des systèmes Research Field Computer science Mathematics » Algorithms Researcher Profile
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suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in
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fait appel à des « pipelines » d'analyse qui associent les technologies de séquençage innovantes aux algorithmes bioinformatiques pour assembler, annoter et comparer les génomes viraux. Le projet
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | about 9 hours ago
Requirements Specific Requirements This project will require a candidate with experience in: Image registration algorithms (non-rigid is a plus) Advanced Python programming skills (especially with Torch / Keras
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for biomarkers in 7T images. - Development of artificial intelligence algorithms and models for the processing and analysis of MRI images/spectra, focusing on the detection of tumor tissue and the quantification
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(formulation, algorithms, applications in structural mechanics), HPC computing, reduced-order modelling, machine learning, Vibrations and structural dynamics, architected materials, Additive manufacturing
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interdisciplinary, and together we contribute to science and society. Your role Multi-omics data integration and workflow improvement Development and application of machine learning-based algorithms
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candidates may be asked to teach: Introductory programming classes Core undergraduate CS classes such as: Human Computer Interaction, Database Applications, Algorithms and Data Structures, Software engineering
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techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems
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to accelerate evaluation of costly simulations Genetic algorithms and other evolutionary techniques to generate a diverse set of high-performing solutions. You will design and implement new optimization