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have some experience with scientific programming, in particular in Python, PyTorch or similar, in particular with respect to advanced data analysis or modelling operations. PhD students at the department
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develops an adaptive AI-guided XR platform for capturing and transferring expert manufacturing knowledge. Your focus will be on developing AI methods for analyzing and modeling human workflows based on data
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address outstanding questions on behavioural evolution in canids. Your work assignments Understanding how behaviours evolve is a long-standing goal in evolutionary biology. Using the domestic dog as a model
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-studies/. Background and description of tasks PhD project 1: The PhD project involves research using invertebrate model systems to investigate the mechanisms by which potential host genome editing processes
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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species like birds and bats. Combining PAM with occupancy modeling allows for large-scale ecological studies, assessing both individual species and community responses to environmental changes. In this 4
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: Verifiable training and trustworthy AI pipelines. Tools for robust data and model provenance in adversarial environments. Methods for protecting training data and end users, including secure data removal and
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production and environmental considerations and facilitate driving on forest land in extremely dry or wet conditions. We will develop different tools. First, we will model soil moisture in the upper soil layer
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-planning of timber production and nature conservation, two important objectives in forestry. The work involves developing knowledge and tools for habitat modelling through 1) mapping existing habitats, 2
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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms