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. The candidate will reduce model uncertainties by producing new large cosmological simulations of the magnetic outputs from galaxies in the ENZO code, which will test realistic implementations of baryonic feedback
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this position, curriculum vitae (including a publication list if available), certificates (certificates should be submitted in English) and contact details of at least two referees through this form https
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knowledge of process systems engineering. The position aims to advance physically consistent and predictive thermodynamic modeling, including the integration of advanced machine learning methods, to support
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research, teaching, and promoting an environment that allows all members of the department to thrive. Principal concentrations include weather prediction, air quality, air-sea interactions, climate modeling
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 9 hours ago
transcriptomics. The main projects are the analysis of gene expression patterns in malignant human tumor samples mostly coming from clinical trials and preclinical model systems, and on the continued development
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intelligence models for the analysis of multispectral remote sensing imagery. The main tasks include implementing computer vision and machine learning methods for the detection and prediction of algal blooms in
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robust descriptors (e.g., water activity, sorption, glass transition temperature, plasticization, porosity, internal distribution) and provide predictive guidelines to rationally select and design drying
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broad range of topics: from model-predictive building control and community battery integration to wind farm optimisation and multi-decade investment planning, we support clever algorithms and data
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on the linguistic analyses provided; o Evaluating the results of the prediction and classification models developed by Loria. Praxiling is a Joint Research Unit (UMR 5267) under the joint supervision of the CNRS and
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on the project can be found here: https://hecustom.eu/ This post will contribute to the creation and validation of a digital twin (with biological bone models) to assess and interrogate the issue of