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), sensing technologies (fiber-optic sensors, DIC), and computer science (machine learning tools). The aim of this Ph.D. project is to develop a novel bridge monitoring technique based on CLCE coating
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integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
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– a journey to become an independent researcher! Throughout the project, there will be multiple opportunities for cooperation with internal and external partners, supervision of Master students, giving
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! Throughout the project, there will be multiple opportunities for cooperation with internal and external partners, supervising Master students, giving oral presentations at conferences, writing high-impact
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, sample and data analysis and write-up of results for scientific publication are part of the PhD process – a journey to become an independent researcher! Throughout the project, there will be multiple
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range of methods, including survey psychology, response-time paradigms, process-tracking techniques (mouse-tracking, eye-tracking), and incentive-based behavioral paradigms and experience in (learning
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studies. Proven experience preparing ethics applications and writing research reports Strong time management and organisational skills, with attention to detail, ability to manage multiple complex tasks
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-funded competence centre for Artificial Intelligence and Machine Learning. It now consists of more than 40 excellent research groups, both in the field of application-oriented Machine Learning and in
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University Hospital, Duke Regional Hospital, Duke Raleigh Hospital, Duke Health Integrated Practice, Duke Primary Care, Duke Home Care and Hospice, Duke Health and Wellness, and multiple affiliations
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detection, diagnosis, and intervention for Autism Spectrum Disorders (ASD) and other conditions impacting social development. Supported by multiple funding bodies (e.g., DFG, BMBF, Rett Syndrome Foundation