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Field
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research spans from measuring and manipulating materials at the micro and nano scale, to the design of world-class sensors and actuators. You will be working in an international environment in one
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mitigating corrosion processes, and on the development of electrocatalysts and electrochemical sensors through the synthesis of materials and the use of advanced electrochemical methods and surface analysis
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analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN implementation topology and its energy efficiency
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). Methods include sensor-based technologies, external and internal exposome approaches, and co-creation and participatory research methods. This PhD position seeks to contribute to and build upon work being
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modeling and simulation experience in PCB design experience in control system design using analog/digital sensors and DSPs/microcontrollers familiarity with HVAC systems and thermal/electrical co-design is a
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locomotion. Apply machine learning and machine vision algorithms to track body and limb movements. Use biomechanical modeling to analyze walking data and fit locomotion models. Operate a force sensor to
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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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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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Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience