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for the next 2.5 years at the interlink of prevention and prediction of wildfire risk, by contributing to the development of a fundamental physical model to understand the process of fire spread for
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work on research projects employing latent variable modeling and risk prediction methods to better understand substance use related morbidity and mortality outcomes (e.g., overdose, hospitalization
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the conditions of crop, pasture, and their environment with advanced remote sensing and geospatial technologies; Develops and refines algorithms and workflows for crop and pasture monitoring, modeling, prediction
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methods to integrate transcriptional and cellular dynamics. Analyze large-scale transcriptomic and spatial dynamics datasets. Work in close collaboration with the team's biologists to test predictions from
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/or High Performance Liquid Chromatography (HPLC) to monitor cell culture media composition, and how to use these measurements to build predictive models of cell cultures able to infer and optimize cell
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the changing climate. The appointee will work in the research team supervised by the Associate Director of Research, on projects that include the prediction of flooding in coastal areas, wave runup and coastal
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Description In this project, we develop machine learning models for prediction of optical properties of chiral molecules based on DFT/CCSD data which we calculate ourselves. We include derivative information by
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multi‑omics data. You will also partner with AI experts to integrate predictive models and advanced analytics into omics workflows. You will work in an expanding team led by Dr. Masoomeh Rahimpour
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with The School of Natural Sciences and the Discipline of Geology, seek to appoint an AIB/E3 Assistant Professor in the area of Earth System Modelling. More specifically, the successful candidate will utilize
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) brief approach (models, data/testbeds), (iv) evaluation plan, and (v) alignment with IDLab research on flexible and deterministic networking at the University of Antwerp (https://www.uantwerpen.be/en