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operation. Translate device concepts into CAD models and engineering drawings, and coordinate component fabrication, procurement and assembly as required. Analyse and interpret experimental data, maintain
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
Text-to-Video Generation Models Supervision : Dr Stéphane Lathuilière (INRIA-UGA) Funding : BPI contract Contexte : Recent advancements in generative AI, and in particular diffusion models [1,2], have
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Including Renewals: 6 months Objectives To develop and validate a hierarchical, time-dependent forecasting framework for the COVID-19 pandemic, integrating heterogeneous epidemiological and data-driven models
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understanding the (1) the epigenetic and post-translational regulation of blood clotting proteins, and (2) mechanisms of thrombosis and inflammation associated with several pathological conditions including but
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) to soft matter or related systems; basic knowledge of scattering data modelling is essential. Data analysis skills and programming experience in Python or MATLAB. Ability to work effectively with multi
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Posting Description POSTDOCTORAL ASSOCIATE, Earth, Atmospheric & Planetary Sciences, to work at the intersection of physical oceanography, numerical modeling, high-performance computing, and machine
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proteostasis, cytoskeletal dynamics, and ferroptotic cell death. This collaborative work combines biochemistry, chemical biology, cell signaling, live-cell imaging, and organotypic brain slice models to dissect
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, addressing practical challenges in flow distribution, heat and mass transfer, sealing, reproducibility and stable operation. Translate device concepts into CAD models and engineering drawings, and coordinate
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Uganda. Building and extending a decision-analytic (Markov) model to estimate the cost-effectiveness of telemedicine with self-monitoring and community medication delivery, relative to standard care, from
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technologies, digital soil mapping/pedometrics, proximal/remote sensing, and geospatial modeling. The ideal candidate will work and collaborate closely within a research team at Texas A&M AgriLife and USDA-ARS