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potentially involving techno-economic analysis and AI-driven models for optimizing design and operation. Activities within project management and co-supervision of graduate students are also foreseen
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of lignin nanoparticles (LNPs). A deeper understanding of these processes will enable the design of innovative applications in drug delivery, nanocomposites, and other emerging technologies. Ultimately
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new design freedoms—such as increased functional integration, improved thermal management, and reduced part count—they also introduce constraints related to material characteristics, process-induced
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and simulation, geometallurgy). Experimental work (with processing of ore and mineral) is carried out in our well-equipped mineral processing laboratory with access to the very latest analytical
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well as system engineering approaches (modeling and simulation, geometallurgy). Experimental work (with processing of ore and mineral) is carried out in our well-equipped mineral processing laboratory with access
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-dimensional statistics, Gaussian approximations, time series, point processes, extreme value theory. The successful applicant will be a highly motivated researcher, capable of working both independently as
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mathematics Appl Deadline: (posted 2025/12/11, listed until 2026/01/16) Position Description: Apply Position Description Postdoc in Algebra-Geometric Foundations of Deep Learning or Computer Vision KTH Royal
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high-temperature systems. Proven ability in process modeling and simulation, preferably using Aspen Plus. Ability to conduct independent research, plan and analyze experiments, and document results
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at the Kollberg Laboratory . You will be a key contributor to in a multi-disciplinary and international project where researchers with expertise in antennas, RF circuits, and digital signal processing collaborate
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industrial value chains. The Production System Division is focused on excellent research and education for design, operation, and maintenance of production systems, aim for sustainable, digital, and