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collection has been the focus of concentrated digitisation efforts during the past eight years, including specimen photography. This new project seeks to harness this dataset using machine learning in order to
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Our group The scientific programmer will be embedded in the Massivizing Computer Systems (MCS) group, which focuses on research in distributed computing systems and ecosystems, and currently spans
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of hydroinformatics, applied mathematical modelling, water sciences, remote sensing, computer sciences, machine learning, civil or environmental engineering with an orientation to water-related problems, from a
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computer systems and for providing technical support to ensure seamless operations. Building the network and systems environment with a combination of standard open-source components, custom services, and
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, together with relevant expertise in areas related to Artificial Intelligence, such as: Foundational Models, Algorithmic Research Machine/Deep Learning Computer Vision Parallel & Distributed Computing Control
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Research and teaching at the Chair of Econometrics & Statistics focuses on the analysis of multivariate time series data. Topics of interest include structural breaks, forecasting, adaptive learning
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both software and hardware. The chance to work with innovative technologies such as AI/Machine Learning. A pleasant and informal working environment with plenty of room for initiative. Job Requirements A
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PhD* in a topic such as animal acoustics, machine learning, quantitative ecology, quantitative biology, signal processing or similar. Evidence of the ability to conduct high-quality research and write
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dialogue with the project and will benefit from learning from the close research environment of the project team. Tasks and responsibilities: Assisting PI in project’s day to day administration, including
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innovation and scientific advancement. The team The Automated Machine Learning team at TU Eindhoven focusses on cutting-edge research to advance the capabilities of machine learning models, while also