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programming Merits: Experience in modelling erosion problems Understanding of critical state soil mechanics, elasto-plastic and elasto-viscoplastic models Experience in numerical analyses (using finite elements
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-loss and highly decoupled FR3 (7-24 GHz) arrays, potentially based on three-dimensional elements and classical Huygen source type of element supporting element-specific band-selection filterig will be
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analyses (using finite elements) of geotechnical problems in field scale, in particular coupled flow-deformation analyses Ability to read and understand Swedish Contract terms Full-time temporary employment
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the driver to actively participate and accept the interventions. A key component in the project will be to practically test feasibility and assess the performance of algorithms and hypotheses in test track
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“Process metallurgy research group ” conduct research and education within the subject areas iron and steel metallurgy, base metal metallurgy, hydrometallurgy and recovery of minerals and metals from
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own research question within this area. The project is mainly intended for quantitative methods but is to some extent also open to qualitative methods. As a doctoral student, you will read doctoral
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will use machine learning methods to develop affinity ligands. These methods have been transformative for protein design, allowing generation of novel proteins which can suit a precise need. In this 4
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We are offering a PhD student position in machine learning (ML) theory, focusing on new methods for training models with a limited amount of data. The student will be a part of a new NEST initiative
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of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
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mining. Project description The knowledge of the mechanical behaviour of tailings is the background of all safety and risk analysis related to tailing dams independent of their construction methods. It is