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Reponsibilities Perform analysis of large-scale quantitative and qualitative datasets as part of research projects. Use of new tools (machine learning, LLMs, OCR) to collect and process data. Work with bank and
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the reference number 27697, via our online portal: Apply now via https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/ For more information visit: www.uksh.de
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16 Jan 2026 Job Information Organisation/Company Universidade de Coimbra Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions
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in computational methods, particularly those with backgrounds in machine learning, artificial intelligence (AI), statistics, bioinformatics, or analysis-acceleration technologies. Candidates should
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Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning, Computational Social Science, Big Data. Relevant skills could include statistical analysis, data
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, peripherals, and applications. Analyzes business requirements and technology needs, manage technical projects, system administration, server administration, application administration, network security, and IT
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has direct societal impact for improving healthcare environments and outcomes. Job requirements MSc Degree in Human-Computer Interaction, Industrial Design Engineering or related fields. Strong
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modalities Experience with signal enhancement, machine learning, or data-driven imaging analysis Track record of publications in high-impact scientific journals, conferences or patents. Experience contributing
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students for certification and employment in Central Service/Sterile Processing. The successful candidate will be able to foster an inclusive and equitable working and learning environment, instructing a
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participate in the development and implementation of Machine Learning algorithms for pattern recognition and automated simulation scenario generation. They will also contribute to the technical evaluation