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multiphase phenomena. The study will combine theory, algorithm development, and computational modeling, with the goal of advancing scalable hybrid approaches for next-generation fluid simulations. Who we
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to the fundamentals and algorithms of spatially and time-multiplexed oscillator-network computing. Duties The PhD student will focus on the fundamentals and algorithms for spatially and time-multiplexed oscillator
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modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring of individual cows. The work includes
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numerical models to improve the simulation of complex multiphase phenomena. The study will combine theory, algorithm development, and computational modeling, with the goal of advancing scalable hybrid
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multidisciplinary research and education environment that advances the state-of-the-art knowledge and fosters the development of highly skilled researchers and professionals. Our research focuses on material
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, develop theory and algorithms for their practical use, and study complexity and performance trade-offs in relevant applications. The project is led by Professor Erik Agrell (IEEE Fellow), whose
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, experience working with the PyTorch framework, documented ability to develop algorithms and implement them in efficient code, and experience in statistical modeling, optimization or numerical methods, as
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knowledge and fosters the development of highly skilled researchers and professionals. Our research focuses on material properties and manufacturing processes for mainly metallic components, specifically cast
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imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes