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for the program. Review all budget requests and projected fiscal needs. Schedule all intercollegiate contests and team travel in accordance with GSC Scheduling and NCAA Model. Review student-athlete eligibility
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carried out include the pre-processing of spatial and temporal data and the implementation of Machine Learning models for the classification of fishing activity. The grant holder will also support the
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conduct research in several areas: analysis of high-dimensional data, Bayesian methods, spatial-temporal models, non-Gaussian modeling, applied research in social science, as well as stochastic models and
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. The PhD (M/F), to be recruited in the context of the ERC StG MULTI-viewCELL, will be working on the development of a new method combining machine learning and biophysical modelling to model embryo
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to the Institute’s needs. Requirements for candidates: Proven experience in advanced hydrological modeling (e.g., conceptual or physically based spatially distributed models), particularly with SWAT+, SWAT-MODFLOW and
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research program combining advanced molecular biology, single-cell and spatial profiling, and in vivo mouse models to uncover how dynamic cell states drive tumor behavior. Beyond the science itself, this is
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Lab aims to reveal how metabolism, oxidative stress, and cell death converge to shape cell fate. For more information about the Henry Lab, please visit: https://thehenrylab.squarespace.com/ For more
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clustering analysis using Voronoï tessellations particle tracking and shadowgraphy measurements, will be used to quantify particle size, velocity, and spatial organisation. These experiments will be
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to sign the contract. More information is available on: https://www.dges.gov.pt/pt/pagina/reconhecimento . Workplan and the objectives to achieve: This work aims to develop a numerical approach based on
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in Data Science and Statistics with expertise in the application of data science to spatial and space-time data from problems throughout the geosciences. The Department of Applied Mathematics and