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Field
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Citizenship or Permanent Residency required Preferred Additional Qualifications • Background in photogrammetry, 3D graphics, or sensor fusion for structural modeling • Track record of publications in top venues
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for production improvement. Explore, build and validate a low fidelity digital twin including more advanced high fidelity configurations critcal for scaling and improvement. Calibrate the models inside the digital
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groups led primarily by Professor Tarek Abdoun and Professor Mostafa Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development
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analytical skills in model evaluation Experience in advanced statistical analysis of results Experience with crop model calibration and evaluation, such as DSSAT, APSIM, or equivalent Insight into analyzing
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analytical skills in model evaluation Experience in advanced statistical analysis of results Experience with crop model calibration and evaluation, such as DSSAT, APSIM, or equivalent Insight into analyzing
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methodology for analysing long-term spatially structured data sets within a joint species distribution modelling framework. For more information on REC, please see https://www2.helsinki.fi/en/researchgroups
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, the project takes advantage of the unique long-term datasets collected in Finland. REC also develops state-of-the-art methodology for analysing long-term spatially structured data sets within a joint species
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 2 days ago
. These one- to three-year fellowships are competitive and are designed to advance NASA’s missions in space science, Earth science, aeronautics, space operations, exploration systems, and astrobiology
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groups led primarily by Professor Tarek Abdoun and Professor Mostafa Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development
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, with a special focus on RNA structure and bioinformatics. This position will focus on the development of methods and algorithms for the comparative analysis of metabolic networks. Your future tasks: We