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Field
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violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic
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Mobasher. It involves a diverse range of activities including: structural and geotechnical modeling, machine-learning model development, structural sensing and health monitoring, conducting physical
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: Support the development of AI and machine learning algorithms for autonomous navigation. Assist in building digital twin models to monitor drone health and mission performance. Contribute to IoT integration
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: Develop and implement machine learning algorithms for SOC and SOH estimation. Analyze large datasets from battery systems to improve model accuracy and performance. Conduct research on predictive analytics
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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learning with synthetic or simulated data. Developing and analyzing new algorithms for AI calibration, run-time reliability monitoring, and adaptive decision-making in wireless environments. Collaborating
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techniques (FTIR, NIR, Raman, …) with machine learning/ chemometrics. Responsibilities of the Position The Postdoctoral researcher is intended to support the soil spectroscopy research activities and digital
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candidate will have the opportunity to collaborate closely with our Danish industrial partners on innovative use cases, including advanced condition-based monitoring in industrial settings and speech
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, atmospheric signals), data fusion across sensing modalities, and development of scalable machine learning pipelines. Work will be entirely computational and based in Seattle, with no field deployment
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focus on advancing human health. Our overarching mission is to define the molecular mechanisms of peripheral tolerance through in-depth immune monitoring. The laboratories utilize primary specimen from