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the Marie Skłodowska-Curie Doctoral Network (ENDOTRAIN). Join Europe’s first doctoral network in digital endocrinology – integrating AI, sensor technology, omics, and clinical medicine to transform diagnosis
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application process here. About the position Are you motivated to develop next-generation research infrastructure at the intersection of robotics, mechatronics, sensor systems, and life science technology? We
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research infrastructure at the intersection of robotics, mechatronics, sensor systems, and life science technology? We have a vacancy for a PhD Candidate at the Department of Mechanical and Industrial
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to the properties of live sensor data: sparse, unevenly sampled, motion-distorted and partially observed Implement and evaluate the resulting systems on embedded hardware and on NIBIO's robot platforms Professional
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: Software Engineering, Sensor Networks and Engineering Computing and the HVL Software Engineering Group (https://www.hvl.no/forsking/gruppe/programvareutvikling-software-engineering/). The research programme
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assessment, smart sensor integration and data analytics, water quality dynamics in transport systems, integration of green infrastructure, and sustainable urban drainage systems Dissemination – Publish in high
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doctoral degree Collect, structure and assess relevant sensor, operational, maintenance, incident and cost data Develop and validate statistical, causal and/or machine-learning methods and turn the results
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the Norwegian Railway Directorate. Duties of the position Complete the doctoral education, including at least 30 ECTS of coursework, and obtain a doctoral degree Collect, structure and assess relevant sensor
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Department of Computer Science and Computational Engineering, and the Department of Geosciences. Research infrastructure is provided via existing data, sensor networks, and established field sites along
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working with heterogeneous datasets originating from different sensors or data sources. Familiarity with forest ecology, biodiversity, or natural-resource applications. Experience developing reproducible