19 condition-monitoring-machine-learning PhD positions at University of Twente in Netherlands
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Vacancies PhD position in “Urban water quality under drought conditions” Key takeaways Freshwater of sufficient quality is crucial to sustain life, development, and the environment and lies
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of reconfigurable nonlinear processing units (RNPUs, [Nature 577, 341-345, 2020[(https://www.nature.com/articles/s41586-019-1901-0). In this PhD project, you will work on the development of efficient machine learning
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Sciences. Through our bachelor’s and master’s degrees, Professional Learning & Development programmes, and interdisciplinary research themes – including Emerging Technologies & Societal Transformations
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, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation
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Research Group Twente: The research focus of the statistics group is on the development of statistical methodology for new data applications and the theoretical analysis of machine learning methods, in
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of the processing system online. Our approach will be to draw on a broad selection of tools including (deep) reinforcement learning, queuing networks, online algorithms and systems engineering. In addition, a large
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apply cutting-edge microscopy techniques to measure pigment behavior under realistic production and application conditions. By characterizing interactions at the nano- and microscale, you will develop
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Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost every device and product we use
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PhD position on Closed-loop testing for faster and better EM evaluation of complex high-tech systems
and Computer Science (EEMCS) uses mathematics, electronics and computer technology to contribute to the development of Information and Communication Technology (ICT). With ICT present in almost every
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used to assess the effectiveness of various water management strategies under a range of climate conditions, supporting the development of resilient and sustainable solutions for agriculture-dominated