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related field from a recognised university. Knowledge and experience in modelling and simulation of microgrids or power systems using ETAP and/or MATLAB/Simulink. Experience in distributed energy resources
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evaluation Knowledge of numerical simulation, for example with land surface or hydrological models Genuine interest in data science and earth sciences Good organizational skills and ability to work both
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student in areas related to Computer Science. Basic experience in health data analysis. Python programming. Knowledge of machine models and deep learning. Intermediate English level. Specific Requirements
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skills: Good knowledge of ML/AI based techniques to develop fast surrogates (deep neural networks) and capability to develop own efficient model learning schemes (deep learning techniques, representation
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related to staff position within a Research Infrastructure? No Offer Description Understanding and modeling material behaviour is central to many engineering challenges. This fully funded Doctoral student
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Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau | Landau in der Pfalz, Rheinland Pfalz | Germany | 5 days ago
with recognized expertise in environmental modeling/ environmental data science. We therefore welcome applications that complement our existing portfolio in an integrative manner. The successful
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Your Job: Chromatography modeling, while crucial for modern bipporcess development, still heavily relies on empirical determination of key model parameters. By combining protein structure
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model. THE PROJECT As part of the Energy Transition, further expansion of wind farms is expected in the North Sea in the next decades. This will likely affect the marine ecosystem and fisheries, but how
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: 281522549 Postdoctoral Associate: Integrating political economy insights into energy modeling D-26-SPI-00009 | Research | Princeton School of Public and International Affairs The Peng group in the School
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have: Ph.D. in Biostatistics, Statistics, Bioinformatics, Data Science, or related field; with (i). technical skills such as Proficiency in R, Python, or SAS for statistical analysis and modelling; (ii