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Field
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Wide Field Science Teams. Duties will include contributing to RGES-PIT science by developing new galactic models/dust models and hierarchical occurrence rates analysis pipelines; preparing papers
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regression, Cox proportional regression model, Poisson regression model) and Big Data analytics (e.g., machine learning, artificial intelligence [AI], text mining, generative AI) Knowledge/Skills/Abilities
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scenarios. The research combines field experiments, AI-based analysis of museum specimens, and advanced climate modeling to provide process-based insights into the ecological and economic consequences
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hydrodynamic models to simulate waves and currents at the field site. Analyze and interpret experimental and numerical data, and disseminate findings through technical reports, conference presentations, and peer
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thermoplastic feedstocks for FDM printing Programming of an existing hybrid FDM printing machine, including printing and milling devices Modelling and optimization of the debinding process Simulation-based design
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structuring of river systems. Familiarity with software and tools for simulating river network dynamics, such as R, Julia, Python, or GIS-based hydrological modeling platforms. Ability to integrate physical
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the design questions using a computational approach to simulate the performance of thermoelectric generators, and subsequently use the model to dimension and design the thermoelectric elements for the heat
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Europe Is the Job related to staff position within a Research Infrastructure? No Offer Description In this project, you will be responsible for conducting numerical simulation campaigns aimed at assessing
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for seasonal prediction using hybrid physics-machine learning models in R&D item Research on Seasonal Meteorological and Oceanographic Forecast Simulator under Development of Integrated Simulation Platform
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simulation environments (e.g., CARLA). • Domain knowledge in ITS, traffic engineering, autonomous vehicles, robotics, or related areas. • Experience using cloud platforms for training and deploying AI models