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of £280,000. Responsibilities include creating and refining models to predict particle behaviour, calibrating them to 95% accuracy, and establishing sensor systems for real-time data acquisition. You will
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, version control) and numerical workflows. Experience programming for data analysis and model workflows (e.g., Python, MATLAB; FORTRAN/C familiarity for model configuration). Demonstrated verbal and written
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to strategic initiatives through advanced analysis, forecasting, and predictive modeling that enhance access to, confidence in, and effective use of institutional data across the College. Kellogg Community
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modeling, machine learning, or data-driven prediction methods applied to environmental datasets. Experience building and maintaining large, frequently updated archives of weather or climate observations
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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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to the lack of generation inertia worsening power system stability. Control of such a complex system relies on detailed understanding and real-time modelling of the nonlinear dynamics resulting from
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Position Information Position Information Working Title Manager, Biophysical Model Design (Temporary) Department Biochemistry-0831 Requisition Number S_260080 Posting Open Date 02/04/2026
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 2 months ago
Automata (CAFE) to considerably reduce calculation times and improve the response of numerical models. The numerical models will include laser-matter interaction, melt, and microstructure prediction models
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pipelines that push technological boundaries for our clients. The Engineer will tackle complex challenges at the intersection of Large Language Models, Computer Vision, and Predictive Analytics while ensuring
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with a strong background in machine learning and LLMs, computer science, and modeling. The candidate will join the project “AI-driven predictive maintenance for buildings: Einar Mattsson (EM) - KTH