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frameworks and economic frameworks identified by partners in the overall project. The programmatic alignment theory, long-term strategic management, and elements of Nature-based Thinking (the organisational
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, multi-omics data integration using machine learning, and potential collaborations with clinical and translational researchers. The project is well-suited for candidates with a background in bioinformatics
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Learning has an open position for a doctoral student with a background and strong interest in deep generative learning and computer vision/remote sensing. The successful candidate will join a project funded
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the field of Machine Elements. The main aim of this PhD student position is to strengthen the newly started research on Triboelectrictive nanogenerator (TENG)-based smart lubrication in Machine Elements
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energy-efficient and sustainable transport systems through world-class research in tribology and machine elements. Friction losses in vehicle systems still account for a significant portion of global
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-quality omics analyses and statistical and machine-learning based modeling, as well as gaining a deeper understanding in extracellular vesicle biology. Work duties and responsibilities The main task for a
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specific research questions: What salient elements in cognitive models represent family forest owners’ perceptions and judgement strategies about forest biodiversity on their ownerships? Do family forest
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an interdisciplinary project funded by the Marianne and Marcus Wallenberg Foundation, we pose three specific research questions: What salient elements in cognitive models represent family forest owners’ perceptions and
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your application: Experience in deep machine learning, finite element modelling, biomechanics, and anatomy What you will do Take courses at an advanced level within the Graduate school of Machine and
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PhD Position in Engineering Materials Project: Development and Characterization of Advanced Sorbents
machine elements. In the undergraduate program, the main two programs focusing on the international profile of the Division of Materials Science are important for the department, namely the EEIGM master's