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compliance-by-design AI architectures and models and validate our solutions across key energy use cases such as energy market optimization (demand response, transactive energy peer-to-peer trading, and
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investigate dynamic phenomena and processes in the Martian atmosphere, combining space craft data analysis with opportunities for modelling depending on the candidate’s interests. The successful candidate will
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will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based on these checks. Primary checkpoints are the Export Control regulation
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publication record in psycholinguistics, Nordic linguistics, corpus linguistics, sociolinguistics, or related fields Experience with R (data wrangling, visualization, statistical modelling) Experience with
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aerodynamic) and structural integrity analysis, primarily using numerical methods and surrogate models. The candidate is expected to work collaboratively in an international research environment. The research
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. The objective is to further develop and validate machine-learning surrogate models derived from high-fidelity multiphysics simulations of reactor transients and quantify how surrogate uncertainties propagate
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interactions. This involves (i) developing predictive machine learning models that forecast user actions and remote system responses across audio, video and haptic modalities, and (ii) jointly orchestrating
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collaboration will be positively evaluated, in particular if the candidate has shown an ability to combine experiments with theory/modeling. Good communication skills are a prerequisite. Required qualifications
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, combining space craft data analysis with opportunities for modelling depending on the candidate’s interests. The successful candidate will have the opportunity to join the science teams of three major Mars
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. The aim is to develop and analyze advanced models that integrate heterogeneous maritime data sources - such as AIS, metocean, emissions, port, cargo, and business data - to improve predictions of costs