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This position creates an inclusive environment to closely work with the Swedish industry in developing methods and tools related to flow-induced acoustics, which is a critical aspect for modern
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research. The methods of our investigations are also diverse and complementary, and range from theory and computer simulations to experiments in subatomic physics. The Plasma Theory group within the Division
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fundamental questions about the particles and forces governing our Universe to energy-related research. The methods of our investigations are also diverse and complementary, and range from theory and computer
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Kahl (Computer Vision, Chalmers), Kathlén Kohn (Algebraic Geometry, KTH), and Mårten Björkman (Robotics, Perception and Learning, KTH). The research focuses on developing novel machine learning methods
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machine learning, computer vision, and materials science. The focus of this position is on development of neuro-symbolic models for the effective behaviour of the complex microstructure of recycled
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for advanced courses, international research visits, and networking across Sweden’s top universities. Information about the research group The Computer Vision Group at the division of Signal processing and
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microanalysis methods to reveal how tramp elements introduced during recycling impact microstructure and properties in aluminium mega-castings. As a PhD student, you will be supported by a multidisciplinary team
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(AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians working collaboratively. Our focus is on developing practical methods that blend traditional disciplines
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of recycled aluminium. More specifically, the project will focus on advanced numerical methods to understand how defects and different microstructures affect the strength of mega-cast components. As a PhD
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long-term, and most often global, perspectives on future renewable fuels for transport. We seek to rigorously analyse the feasibility of energy transitions, utilize empirical as well as estimated data