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encompasses the creation of insights that allow the development of context-aware, distributed, and embedded cyber-physical systems, with a particular focus on Internet-of-Things (IoT) and the computing
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precision machining, tools are prematurely discarded to avoid the risk of costly non-conformities. This creates a large loss of value of strategically valuable raw materials and waste of energy related
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to carry out high-quality research on the modelling of power system balancing process for future sector-coupled European energy systems. The task will include assessment of reserve requirements and
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science applications Computational Atomic-scale Materials Design with a focus on materials modeling and discovery with electronic structure calculations and machine learning Luminescence Physics and
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The assessment will take into account the following criteria: Willingness and ability to spend one year in Australia as part of the Alliance PhD program is mandatory. Experience with process technology and
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relation to the expected loading conditions during the lifetime of a window. Your primary tasks in the PhD project will be to: Identify relevant material and process parameters for characterization of glass
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multi-physics modelling, autonomous materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all levels, ranging from BSc, MSc, PhD
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Neural Networks (SSM-SNNs). The project includes the co-design and integration of a RISC-V processor for hybrid neuromorphic computing. The research aims to develop ultra-low-power computing chips
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for the integrated scholarship, you are (or are eligible to be) enrolled at the faculty’s master programme in Physics. Students on the integrated programme will enroll as PhD students simultaneously with completing
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precision machining, tools are prematurely discarded to avoid the risk of costly non-conformities. This creates a large loss of value of strategically valuable raw materials and waste of energy related