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, we aim to generate knowledge towards the development of sustainable pest and disease management solutions based on conceptual theory and empirical eco-evolutionary, molecular, and genetic data that can
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management solutions based on conceptual theory and empirical eco-evolutionary, molecular, and genetic data that can meet the needs of current and evolving plant production systems. Read more about our
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, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
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, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems. Project description This PhD project is linked
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provides a unique opportunity to work at the intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations
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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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absorption/fluorescence and scattering experiments at X-ray free electron lasers. Your focus will be to derive new algorithms for interpretation of the scattering data by introducing chemical force-fields via
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. The successful candidate holds/or are about to receive a Master of Science degree in computer science, data science, or a related area, and have strong background in algorithmic design, data mining, machine