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data Development of algorithms for infection and evaluation of infection hotspots in the plant population Coordination of the scientific interface to the project partners with regard to entomological
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://reallabor.offshore.uol.de/en/ ). Within your PhD, you will develop wind farm control algorithms that can contribute to providing system services with a focus on active power and frequency control while simultaneously
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advanced statistical machine learning, reinforcement learning, and gen-AI-driven decision models for supply chain and operations optimization. • Design scalable algorithms for demand forecasting, risk
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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward
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modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
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motors and braking technology, high-torque density axial flux electrical motors, development of servo controllers and algorithms, and special electrical machines such as superconducting electrical motors
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novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic engineering, embedded systems design
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the utility and the robustness of different explanation strategies. A large focus of this project will be on leveraging novel and interpretable approaches in applied domains such as algorithmic fairness and
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of probability, statistics and optimization. * Proven expertise in the implementation and testing of algorithms. * Strong programming skills in R or Python. * Familiarity with data science and visualization
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our software development team, developing novel scientific algorithms and applications in the areas of spectroscopic analysis and mining of the science data catalogues extracted from the pipelines