28 algorithm-"Multiple"-"U" "NTNU Norwegian University of Science and Technology" PhD positions in Sweden
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to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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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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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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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