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for High-Frequency Financial Time-Series Data Introduction Are you passionate about using advanced machine learning techniques to solve real-world problems in financial trading? Do you enjoy working with
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Your job We are seeking a PhD candidate to drive the transformation of food product development through the integration of high-throughput experimentation (HTE), data science, and food processing
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developmental data and ecological validity. Infant data will be acquired in collaboration with Dr. Tessa Dekker (University College London) and Dr. Ingmar Visser at UvA. The project thus aims to quantify and
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if the necessary clean energy and energy infrastructure is available at competitive costs. Large-scale investments in the energy sector meanwhile get off the ground only if industry is prepared to electrify its
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data mining algorithms that can integrate and combine multi-modal data acquired from a variety of sources (smart watch sensors, spatial maps, building information sources (drawings and digital models
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of Arts The Faculty of Arts is a large, dynamic faculty in the heart of the city of Groningen. It has more than 5,000 students and 700 staff members, who are working at the frontiers of knowledge every day
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-modal prior information Job description The project is part of the IMAGINE open innovation lab (https://research.umcutrecht.nl/news/imagine-takes-off/ ), and aims to develop novel computational methods
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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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(scientific) programming, and an affinity with network analysis in particular. You are able to work with very large data and have the creativity and curiosity to develop AI models for network analysis
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populations are to be expected, especially given the large quantity of future planned OWFs. Also we would like to test the attraction versus production hypothesis: are fish simply attracted to the monopiles