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at a computer for large portions of the day; repetitive motion; occasionally positioning patients over 25 lbs. Shift Monday – Friday, Day Shift; 7:30-6:00pm (40 hrs/wk), 4x 10-hour shifts Job Summary We
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analysis. • Hydrological and hydraulic simulation. • Machine learning, including unsupervised clustering and predictive modelling. • Working with large, complex, multi-source datasets using MATLAB, Python
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publication record. Outstanding data analytics, mathematical, and computer modelling skills. Excellent interpersonal communication and oral presentation skills in English Self-driven and strong team spirit Open
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developments in sensor design, dataset transmission, data analysis, and numerical modeling to distinguish between normal and abnormal features. Here, the goal is to develop machine learning algorithms
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning
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to their existing curriculum in machine learning, data science, and computational modeling of cognition. Our priority is to attract candidates who are strong in relevant technical areas and who can teach Python-based
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employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ The department's research on responsible and human-centred artificial
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different backgrounds. This position requires that you have graduated at Master’s level in in computer science, media technology, computer engineering, human-computer interaction, visual learning and
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Computer Science, Data Science, and Artificial Intelligence, in both our West Lafayette and Indianapolis locations, as well as graduate MS and PhD programs. For more information, see https://www.cs.purdue.edu
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science » Computer systems Computer science » Modelling tools Computer science » Informatics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 May 2026 - 23:00 (Europe/Paris