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Interaction with a design and data-oriented perspective. Experience in research in the domain of affective interaction design Background in large-scale data engineering Personal or professional experience
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University of California Agriculture and Natural Resources | Riverside, California | United States | about 20 hours ago
extension support for small-scale, diversified, and historically underserved farmers. Areas of focus include on-farm production challenges such as irrigation, nutrient management, and pest management
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. For more information on the work of the group please see https://www.maynoothuniversity.ie/physics/our-research. This position is part of the CARINA project which is funded through a Research Ireland
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several major types of mobility modeling, with the aim of improving their respective efficiency and usage: four-step models, multi-agent systems and a mobility model developed in the PhD thesis of Louisette
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Posted by Kate Stuart on Wednesday, March 18, 2026 in Job Opportunities . The Cruchaga lab (https://cruchagalab.wustl.edu/ ) at Washington University School of Medicine has a
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for GHz speckle experiments - 29,25 hours/week The position X-ray Photon Correlation Spectroscopy (XPCS) enables the study of nanoscale and atomic-scale dynamics by analyzing fluctuations in coherent X-ray
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community.Together, we’ll create meaningful impact at a scale few others can match. Connections working at The Ohio State University More Jobs from This Employer https://main.hercjobs.org/jobs/22154743/extension
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The School of Mechanical & Aerospace Engineering (MAE) is a robust, dynamic and multi-disciplinary international research community comprising of world-class scientists and bright students. MAE
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. The selected postdoctoral researcher will play a central role in developing computational, data-driven, and analytical frameworks to quantify and evaluate the multi-dimensional impacts of data center growth. The
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experiment on a metric-scale concrete wall, using the multi-physics NDE probe integrated onto drone platforms. Expected Results A Python-based multi-physics Maching Learning framework for NDE characterization