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Field
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willing to work in a collaborative environment. Preference will be given to those with (i) strong background in quantitative methods, geospatial methods, AI and machine learning; (ii) experience in high
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of dissertation topics: Developing Remote Sensing–Based Indicators of Landscape State and Change Using Data-Efficient Machine Learning Across Scales Profile of the graduate The graduates have deep theoretical
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devices for medical imaging and reaction monitoring, as well as for the development of sustainable photocatalysts. In this role you will develop machine learning (ML)-accelerated quantum mechanics in
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Interaction / Human-Centred Artificial Intelligence Help shape the future of work. This PhD project investigates how collaborative AI agents can support communication, learning, and shared understanding in blue
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administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Job vacancy starting: 01.02.2026 (MM-DD
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intelligence, data analytics, uncertainty analysis, probabilistic modelling, or statistical learning you have experience working on relevant research or project activities involving machine learning or data
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machine learning packages (e.g.PyTorch). Completed academic courses in AI or machine learning. Interest in societal, ethical and philosophical questions. We consider it an advantage if you bring one or more
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sciences, law, and philosophy. Four WPs address citizen-empowerment-scenarios (CES) in healthcare, mobility, public governance, and healthy living. Each PhD position is embedded in one work package and
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the world. Each of the four campuses (two in Chicago, one in London, and one in Hong Kong) reflects the architectural traditions of its environs while offering a state-of-the-art learning environment. Chicago
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome