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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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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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, such as decision rights, transparency, human override, and visible oversight, shape perceptions of legitimacy. A particular focus is the boundary between AI-augmented leadership and de facto algorithmic
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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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algorithms and techniques at the MAC layer for fast anomaly detection, failure prediction, autonomous recovery, and performance resilience. Service-aware MAC layer techniques – develop novel MAC-layer
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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
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. Thus a background in fluid mechanics (marine hydrodynamics or aerodynamics) is required. Knowledge of measurement technology and relevant sensors, as well as industry experience from the industry
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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high