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analytics solutions; interoperability standards (e.g., HL7, FHIR); biomarker or phenotype modeling; Bayesian or predictive modeling; or the analysis of genomics or other omics-scale data. Experience
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of descriptive and predictive mathematical models. Examples of current and relevant problems in modern society that can be treated using such methodologies are ensuring the efficiency of industrial and
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observational data, and the application of advanced methods for longitudinal and prediction modelling. You will also conduct methodological research on Bayesian methods and other innovative methodology
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on building dynamic system models for both the energy conversion technologies and the greenhouse climate, integrating these into a unified framework suitable for state estimation, predictive control, and
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analyze particle precipitation from low-altitude spacecraft, in conjunction with particle and wave measurements from near-equatorial spacecraft, and theoretically model electron precipitation driven by
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al. 2019] and point-force Lagrangian models, with advanced post-processings [Vegad2024]. This work will be carried out with the YALES2 high-performance platform. Where to apply Website https
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French National Research Institute for Agriculture, Food, and the Environment (INRAE) | Villenave d Ornon, Aquitaine | France | 3 months ago
be to develop predictive models dedicated to the ecological transition of agriculture. The project extends the understanding of links between metabolism programming and trade-offs with plant
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | about 1 month ago
the discrepancy between theoretical predictions and the actual observed behavior. The objective is to develop model-based artificial neural network tools that combine the strengths of traditional numerical
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questions for both Biogeography and Quaternary Palaeoecology, and the answers provide the basis for predictions of ecosystem and species response to future climatic change. We are looking for PhD candidates
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predictive control, optimization-based decision frameworks, and data-driven performance modelling. The overall goal is to develop computational methods that enable efficient and intelligent operation of wind