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, Physics , quant-ph , Quantum Science + Quantum Information Science + Quantum Optics + Theoretical Physics , Quantum Sensors , Theoretical Particle Physics , Theoretical Physics, HEP-Phenomenology (hep-ph
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academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and
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support research in: • Transportation systems modeling and simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling • Large-scale computing, cloud-native analytics
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systems architecting AI/ML-driven clinical and operational decision support Digital health and learning health systems Healthcare operations, resource allocation, and workflow optimization Network, graph
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and maintenance of monitoring buoys and related sensor systems. Apply image analysis and machine learning techniques to ecological datasets. Develop and implement multi-platform monitoring frameworks
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-driven, machine learning approaches. The biomass data product will be validated by data from an international network of ground-truth forest sites (GEO-TREES, geo-trees.org). The developed algorithms thus
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quantum networks, where one bit of information is encoded in the quantum state of a single photon. You will be part of a team of 10-12 people between senior staff, PostDocs and PhD/Master students
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research in deep learning models for multi-sensor satellite data (e.g. SAR, SMAP) within a large international research project on AI-driven solutions for groundwater management. Expected start date and
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simulation, including O/D modeling, multimodal network modeling, agent-based or behavioral modeling Large-scale computing, cloud-native analytics workflows, and data engineering for mobility platforms AI/ML
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systems • Healthcare operations, resource allocation, and workflow optimization • Network, graph, and agent-based modeling for care delivery • Health equity, patient access, and system resilience • Multi