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At the Technical Faculty of IT and Design, Department of Sustainability and Planning (PLAN), a Postdoc position in Satellite Data Processing and Machine/Deep Learning is open for appointment from
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learning on graphs, including knowledge graphs, social and biological networks, financial networks, temporal and dynamic graphs, uncertain graphs, explainability and fairness of deep learning methods
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probabilistic machine learning and geospatial sciences. Limited teaching may be arranged, if mutually agreed, in exchange for a contract extension. Qualification Requirements Applicants must hold a PhD degree in
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Requirements Applicants must hold a PhD degree in Machine Learning, Artificial Intelligence, Computer Science, Statistics, or a closely related field. A strong research background and programming experience
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networks, financial networks, temporal and dynamic graphs, uncertain graphs, explainability and fairness of deep learning methods on networks. The aim will be publishing several research papers at top-tier
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into global environmental changes, and ecosystem sustainability Experience with deep learning, radiative transfer modeling Teaching and supervision experience Who we are At the Department of Agroecology, our
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operation of the laboratory equipment and day to day running of the microwave pyrolysis laboratory Your profile The applicants should hold a PhD in applied chemistry, chemical engineering or similar. Both
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to explore new analysis methods using deep learning. Depending on the interest, it is also possible to be involved in the wet lab. Professor Tiwari also leads the Center for Integrated Multiomics in Precision
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materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all levels, ranging from BSc, MSc, PhD to lifelong learning students. We have about 300
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comfortable working with deep learning frameworks such as PyTorch or TensorFlow and have experience with speech representations like phonemes or learned units, as well as familiarity with ASR systems. Strong