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degradation modes. Evaluating suitable sensor technologies and data sources for acquiring relevant metrics. Developing tools and algorithms to automatically analyse sensor data, assess asset condition, and
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13.01.2020, Wissenschaftliches Personal PhD position at the Chair of Algorithms and Complexity. Candidate shall work on approximation algorithms for scheduling problems in parallel and distributed
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the academic staff at SIT. We are looking for PhD students to work on projects on stochastic optimisation algorithms for hyper-parameter tuning in Machine learning. The successful candidate will explore
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: • Image processing and sensor data analysis, ideally with HSI or other imaging technologies. • Machine learning and artificial intelligence, especially classification and segmentation tasks. • High
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field. Research Field: Fluid dynamics, control engineering, or dynamical systems. Required Skills/Qualifications: Experience with experimental methods (laboratory setups, sensors, data acquisition
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single electron spins in diamond as sensors to explore magnetic phenomena at the nanoscale. This doctoral project will center around the development and application of scanning magnetometry at ultra-low
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. Organic electronics offer a promising alternative to inorganic electronics for large-area applications, particularly in displays and flexible sensors. Among these devices, Organic Thin-Film Transistors
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capabilities needed for truly sustainable operations. Research Question: How can AI-enhanced digital twin technologies with advanced optimisation algorithms transform manufacturing processes to achieve
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
, IoT/sensor data, TPTC, LPS, LBS), (d) development of rich VLE prototypes through creation of serious gaming scenarios using state-of-the-art technologies, and (e) validation in large-scale realistic
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Inria, the French national research institute for the digital sciences | Villeurbanne, Rhone Alpes | France | 5 days ago
, 3], significant challenges related to running complex AI algorithms such as Deep Neural Network (DNN) inference on lightweight platforms with limited computational power and relying on potentially