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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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reuse of energy systems analysis processes. In line with FAIR and Linked Open Data principles, you will design interfaces that enable the smooth processing of big data in the context of scientific, AI
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while reducing waste, we are at the forefront of innovation. Moreover, employing advanced techniques like artificial intelligence and machine learning, we are revolutionising material production, making
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Your Job: This position focuses on building, operating, and testing superconducting quantum devices. Your tasks in detail are: Design and fabrication of superconducting quantum circuits Setting up
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future climate scenarios. Your research will contribute to understanding the effects of climate change on renewable power generation and its impacts on energy system design on a global scale. Key
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The Doctoral Training Programme in the Learning Sciences aims to support excellent students in designing and conducting state-of-the-art dissertation projects in the multidisciplinary field of the Learning
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systems on different temporal and spatial scales. For our Research Group Applied Optimization we are looking for a PhD student: New Deep Learning - based Framework for Energy Modelling: Combination
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, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks Requirements: excellent university degree (master or comparable) in computer engineering or electrical
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mobility, and create a collaborative environment. TUD and the CRC embody a university culture that is characterized by cosmopolitanism, mutual appreciation, thriving innovation and active participation
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks