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Postdoc: Machine learning for wind flow prediction in coastal dunes Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline: 6
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inference), and automated machine learning. holding (or close to acquiring) a PhD degree in Computer Science, Artificial Intelligence or a closely related field; strong research vision and an academic mindset
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the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy to consider candidates in one of the two fields who can demonstrate a strong basis for working in this cross
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We are seeking a postdoctoral researcher with a curiosity-driven record who works at the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy
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across the broader TU Delft research community. Job requirements PhD in computer science, AI, machine learning, data science, network science, computational social science, or a related field. Expertise in
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interested in mentoring and supporting MSc and PhD students. You are a machine learning enthusiast (and realist). You love coding and have proven experience in e.g. Python, Matlab, JAVA, C#. You can present
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to learn about, (road) network traffic flow theory and simulation. You are interested in mentoring and supporting MSc and PhD students. You are a machine learning enthusiast (and realist). You love coding
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researcher to work on systems theory for energy-based learning. What are you going to do? As a postdoctoral researcher, you will develop and analyse new algorithms for energy-based learning of complex systems
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, with a particular focus on the iron and steel sector. By using TROPOMI observations with advanced machine learning techniques, the project will provide independent information on emission patterns and
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As a postdoctoral researcher, your primary responsibilities will be: Develop machine learning and deep learning models, with a strong focus on computer vision, for the characterisation and