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. Tools for robust data and model provenance in adversarial environments. Methods for protecting training data and end users, including secure data removal and machine unlearning. Machine unlearning
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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
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Modelling and Cognitive Systems, as part of the Linköping University Semantic Web group. The Semantic Web group conduct cutting-edge research in several aspects of the Semantic web, including ontology
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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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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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, flexible and adaptable distributed system of systems. Example of specific problems are: -Information interoperability supported by ontologies. -Unified data models for operational environmental impact -SOA
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qualifications Marine biogeochemical processes Hydrodynamic processes related to ships, turbulence, or mixing Oceanographic modelling Data analysis and programming (e.g., MATLAB, Python, or R) Interdisciplinary
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aims to build predictive and physical binding models of protein – DNA interactions using high-throughput and quantitative biochemical binding data across hundreds of thousands of sequence variants
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on the following criteria: Knowledge in electric power engineering, power electronics, and power system analysis Experience in modelling, simulation, and experimental work Proficiency in Swedish and English, both