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renovation construction work · evaluate (numerical or data driven) solutions for automated coordinated planning · develop and evaluate self-learning interactive visualisation technologies
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address issues like data privacy and ownership, distribution of responsibilities and accountability, and technology access on organisational, project and district level, and explore how digital technologies
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design, coordination) and non-technical (e.g., streamlined governance and re-engineered processes) natures. The PRE-MADONA project offers a game-changing solution by leveraging data-driven methods
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, Industrial Engineering, Computer Science, or Machine Learning. Solid experience with quantitative optimization methods, including (but not limited to) mathematical programming and stochastic dynamic
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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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weather prediction using Machine Learning approach (hybrid forecast). The app is also expected to be equipped with seasonal forecast for agricultural planning. You will co-design the short-, medium-, and
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Machine Learning Problems > Constantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation or signal > Experience in setup of research
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education and research. The applicant is expected to have: A MSc or equivalent degree in Microelectronics, Computer Science, Electrical Engineering, or a similar field; Expertise in your field of study, in
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mechanics at the atomic scale. In this project, the University of Groningen will develop an array of state-of-the-art machine learning potentials for multi-component alloy systems that are relevant
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are seeking a motivated, enthusiastic, and curious PhD candidate to join our Health Technology and Services Research (HTSR) section at the Faculty of Behavioural Management and Social Sciences. At HTSR, you'll