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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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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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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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at: https://www.umu.se/en/department-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models
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this project, we will develop new algorithms and computational schemes as well as further develop existing computational frameworks in the team. We will focus on two related frameworks in the project
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Biochemistry advances multiphase flow and separation science to accelerate industrial innovation and implementation. About the research project The project aims to develop hybrid quantum–classical approaches
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development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en/department
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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