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A PhD position starting November 1, 2025 (with some flexibility in both directions) is available at the University of Southern Denmark (SDU) for research in an exciting project in algorithmic
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specialized algorithms supported on solid theoretical foundations and with a focus on challenging aspects of very high-dimensional datasets, such as datasets encountered in the computational biology and
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to the success of the whole institution. The Faculty of Computer Science, Institute of Theoretical Computer Science, thenewly established Chair of Algorithmic and Structural Graph Theory offers a position as
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investigate new algorithmic principles that make learning agents adapt to non-stationary environments in an autonomous manner. The expected outcomes are new theoretical insights about the algorithmic roots
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and skilled individual to join our cross-disciplinary research team studying the ecology of vision. Our goal is to better understand the inter-relationships between vision, evolutionary processes
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address domain-specific challenges in biomedical applications. The PhD project will focus on translating and enhancing cutting-edge algorithms from AI research into concrete applications in biomedical
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-body positron emission tomography (PET) with magnetic resonance imaging (MRI). In conjunction with the development of algorithms, dedicated software and hardware-based simulations will be developed
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algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical optimization of QML algorithms Noise mitigation in relation
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
predictive machine learning model; iii) based on the machine learning algorithms, develop PBF-LB Mg alloy with defined microstructure, improved mechanical and corrosion properties. Research stays are planned
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available (>1.1 million people). The goal is to establish how many archaic human groups contributed to our genomes. Your task is to infer key parameters of the archaic human evolutionary history such as