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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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on computer networking and distributed systems, computer security and privacy, and software engineering. Both research and education are conducted in close cooperation with international, national, and regional
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(e.g. in automotive applications) using, for example, vibration and acoustic signals. Research questions include method development for fault detection and isolation, damage estimation systems, including
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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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magnets with functional, high-temperature magnetoelectric coupling. The theory position in the group of Sophie Weber will focus on (a) development of group-theoretical methods to rapidly identify and design
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rotation forestry towards continuous cover forestry methods is debated in Scandinavia as a way forward to increase biodiversity and climate resilience. This postdoc project will be based on empirical field
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to methods and principles aimed at understanding and modelling the mechanics of deformable bodies. Solid mechanics is a core discipline in mechanical engineering and is of fundamental importance to many other
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, especially TRP- and KCNQ-channels. To achieve this ambitious goal, we will employ an interdisciplinary approach centered on structural biology and biochemical methods. The recruited individual will conduct
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of mathematical areas. The position will be placed at the Department of Computer Vision and Machine Learning (CVML) at the Mathematics Centre (https://maths.lu.se/). Mathematics Centre is a department
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national and European projects that focus on both fundamental and applied research. The Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) addresses data-driven methods to gain