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of the project “PROSPER: Predictive models for sustainable protein recovery”, funded by FEDER and by National Funds through FCT (Operation No. 15391 — COMPETE2030-FEDER-00907300), under the following conditions
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selection criteria You must have strong competence in artificial intelligence, signal processing, modelling, instrumentation, or control, including good programming skills. This background is typically
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into European energy system models based on the institute's own open-source FINE framework https://github.com/FZJ-IEK3-VSA/FINE . Your tasks in detail: Implementing geothermal plants with material co-production
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response using large public datasets and modern predictive modeling Integrate CIN signatures with functional dependency resources to shortlist candidate vulnerabilities for validation Contribute to open
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kidney disease in adults: assessment and management. Clinical guideline [CG182]. Tangri N, Stephens LA, Griffith J et al A Predictive Model for Progression of Chronic Kidney Disease to Kidney Failure. JAMA
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
to perform disease modeling and critical analytics in response to infectious disease outbreaks. Duties will include helping to implement predictive and analytic models of infectious disease using Python and R
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scientific leaders and entrepreneurs. Job Summary This role reports to the Director of Finance and the Senior Associate Dean and Chief Operations Officer. The Financial Systems and Controls Architect
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French National Research Institute for Agriculture, Food, and the Environment (INRAE) | Estrees Mons, Picardie | France | 2 months ago
controlled conditions (ecotron, growing rooms), whether within INRAE, locally or nationally, or with partners of the cross-border joint research unit BioEcoAgro. Where to apply Website https://jobs.inrae.fr/en
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and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in
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numerical models and machine learning tools to predict loads, assess structural responses, and identify damage under extreme conditions. By combining computational simulations with data-driven approaches