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transitions, flow dynamics, stratification) inside thermal storages containing PCMs? How can we describe via validated multi-physics simulation models; heat transfer, flow behavior, and phase changes? Your task
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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science, computer science, applied mathematics or a related field a strong background in machine learning, material modeling, and metals processing, modeling and simulation (This will be a clear advantage
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, energy-related datasets. Proficiency in Python, MATLAB, and/or Julia for modeling, simulation, and data analysis. Familiarity with GIS tools (e.g. QGIS), time-series databases (e.g. InfluxDB), and version
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in the SPG. We will make use of models of different complexity up to complex Earth System models, and modelling efforts for different past periods. A personalised training programme will be set up
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home office allowance of €2 per day. Reimbursement for sustainable commuting: walking, cycling, and public transportation. A monthly internet fee of €25. An Options Model in which you exchange benefits
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with researchers from climate physics, hydrology, sustainability science and complex systems dynamics and apply a range of different models. Starting from the recent AMOC tipping simulations performed
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aims at developing tools using large language models (LLMs) for the correction of misinformation about climate change in social media. The successful candidate will develop innovative tools leveraging
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inductive biases, we aim to identify key mechanisms that drive rapid learning in the visual system. The goal is to create a robust mechanistic neural network model of the visual system that not only mimics
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. To achieve your goal, you will use different approaches, including but not limited to: RNA sequencing techniques (e.g. RNA-seq, TT-seq, PRO-seq); Proximity labeling approaches and pulldowns; Chromatin