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Field
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learning algorithms for early damage detection, health indicator extraction, and remaining useful life prediction. The successful candidate will take a leadership role in experimental integration and data
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and elicitation of informed prior distributions; Critical assessment of default prior distributions; Organizing a many-statisticians challenge and workshop; Studying model-averaging, effect size
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well as collaborate with PhD candidates. You'll design experiments using our robotic platform, analyze tactile data patterns, implement real-time control algorithms, and validate performance across diverse scenarios
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work with Dr. Anna Dawid and her research team. The position is set in the exciting, friendly, and interdisciplinary environment of the aQa (Applied Quantum Algorithms) group, which is a team of faculty
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-time control algorithms, and validate performance across diverse scenarios. You'll be part of the Tactile Machines Lab, which is a dynamic, interdisciplinary group of researcher bringing together
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on the OpenMS Project. The selected candidate will develop a local platform that enables users connected to MV transformers to exchange information with other users and the distribution system operator
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manufacturing technologies, including light-based (DLP) and extrusion-based (3D fiber deposition) approaches. You will take the lead on applied physics, mechanics, manufacturing processes, and algorithm/coding
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on the following activities related to Bayesian inference in factorial designs: Construction and elicitation of informed prior distributions; Critical assessment of default prior distributions; Organizing a many
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in using AI technology in citizen-state interactions. How can we design fair algorithms, and how can we govern AI-related risks? The position is funded for a period of 18 months, preferably starting
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, ranging from regional to global scales. How these systems will take shape, in terms of technologies, infrastructures, (geo)spatial distribution, scale and related investment needs matters for how and which