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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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yield new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in
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computing systems design and realization, including machine learning (ML) and artificial intelligence (AI) applications including autonomy, sensing and communication, advanced manufacturing, and decision
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open PhD positions throughout the year. Learn more about PhD opportunities at the Hertie School and the relevant application deadlines here . Further information on the application procedure can be found
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Forecasting the Future of Biodiversity: Cutting-Edge Approaches to Population and Community Dynamics
: How can tools like passive bioacoustics revolutionize wildlife monitoring? We offer cutting-edge training in statistical modelling, machine learning, and ecological forecasting, and our lab works across
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science and information science techniques. Several areas of computer science and mathematics play important roles: data management and engineering, machine learning and data analytics, signal and image
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opportunities, benefits, community events, and other resources available via the office of Graduate and Postdoctoral Success at BU: https://www.bu.edu/postdocs/ Skills and qualifications A PhD in epidemiology
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to teach in at least one of the thematic areas listed above. Additional desired qualifications include a PhD degree, the ability to teach across multiple areas of the curriculum, strong engagement with
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analysis Background in biomedicine and digital pathology What we offer Embedding within a computational team, with extensive experience in computational biology and machine learning. Embedding within
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Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 2 days ago
new insights into food-effector systems, sophisticated and tailored computational methods are needed. This project aims at combining probabilistic machine learning methods with prior knowledge in