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equivalent), preferably within civil and environmental engineering, statistics, industrial ecology or data science with a passion for sustainability. We welcome candidates with postdoctoral experience
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approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers
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forecasting. You will get the opportunity to participate and influence the development of advanced forecast solutions combining weather forecasts and novel machine learning/statistical forecasting methods
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statistical analyses for the tasks. Based on your competence and interests, your tasks will include: Develop and use epidemiological models (for example regression models or SIR-models), including for “what
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statistical and machine learning techniques for dynamic energy system modelling Develop advanced optimization algorithms for building energy management and control (e.g., MPC, RL) Develop and evaluate digital
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frameworks. Strong knowledge of probabilities and statistics. Ability to work in a UNIX environment. Demonstrated the ability to publish in the international peer-reviewed research literature Proven ability
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environment with 400 employees and 10 research sections spanning the scientific disciplines of mathematics, statistics, computer science, and engineering. We offer education ranging from bachelor's degrees
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, scipy, scikit-learn, pytorch, pytorch geometric, etc.). Proficiency in statistics and graph machine learning, including the ability to build and deploy models, and evaluate their performance. Software
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on developing machine-learning-based or statistical emulators to approximate key outputs of complex Earth System Models, with the aim of enabling efficient uncertainty quantification, sensitivity analysis, and
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at the Dynamical Systems Section is very wide ranging. From foundational research in work on statistical forecasting, modeling of spatial and temporal processes and time series analysis to applied research in wind