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datasets (e.g. ground-based radar measurements and weather station data) Contribute to the development and application of numerical models Assess uncertainties for future sea-level projections Publish
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breed x system interactions. Including e.g. milk-based parameters according to other WPs, production system specific early prediction models for the control of endoparasites will be developed
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crosslink highly diverse bioeconomic production systems and to control them in a knowledge-based, adaptive and largely automated manner. We conduct research in dialogue with society, policymakers, industry
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years based on satisfactory performance and availability of funding. The Postdoctoral Research Scholar will join a team, under the direction of Prof. Michael Woodford, who studies the cognitive
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on building dynamic system models for both the energy conversion technologies and the greenhouse climate, integrating these into a unified framework suitable for state estimation, predictive control, and
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offer a deeper analysis of this class of stochastic processes concerning their stochastic and statistical analysis and to propose some non-Gaussian stochastic models, based on (generalized) Hermite
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to offer a deeper analysis of this class of stochastic processes concerning their stochastic and statistical analysis and to propose some non-Gaussian stochastic models, based on (generalized) Hermite
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. Key Responsibilities: Develop and implement perception and control algorithms for robotic arms and embodied AI systems. Assist in integrating multimodal AI models (vision, language, force sensors) with
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—influence emotional activation, cognitive information processing, and subsequent economic behavior. The empirical part of the work will be based on a controlled laboratory experiment in which auditory stimuli
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(Lua/Java), agent behavior modeling, event handling, and API-based integration with external AI systems. Experience with distributed systems, reinforcement learning, or simulation environments (e.g