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systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization
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research will primarily be based on farms and at field experimental sites in both northern and southern Sweden. The doctoral student will work with established and new experiments investigating forage
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calibration, uncertainty quantification and machine-learning-based surrogate modelling have been developed for nuclear fuel-performance simulations. You will further develop these methods to enable faster and
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directions: Long-term Autonomy in Uncertain Environments a. Agentic Planning and Reasoning - Semantic Mission Planning with Foundation Models - Foundation models based task decomposition - Event-driven task re
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., analysis, statistics and modelling), proficiency in the R programming language (of particular value if coupled with TMB), familiarity with version control pipelines, preferably experience in fisheries stock
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control with Git, typesetting with LaTeX, use of Linux computers; Experience with convolution and transformer-based neural networks for image analysis; Experience with graph-based methods, and graph
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. At the Division 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
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offers a unique interdisciplinary training environment bridging experimental mass spectrometry-based proteomics and AI-driven protein structure modeling. The student will have access to existing large
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as well as experimental work in immersive or intelligent indoor environments experience in quantitative data analysis and modeling methods, such as agent‑based modeling and AI‑supported behavioral
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processes, and point process modelling is considered a merit. Good command of English, both written and spoken, is required. The candidate is expected to take an active role in developing the doctoral project