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Field
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• Enhancing and deploying computational platforms such as Cornell TEAM-Cities, CATChain, uTECH, etc. • Working with geospatial and mobility datasets (GPS trajectories, transit feeds, sensor data, demographic
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to be essential. Certain conflicting objectives then arise (computation time, optimality of the solution, design and implementation time of the algorithm used, etc.). For the engineering researcher, who
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/algorithmic modelling. Experience with multidisciplinary IoT systems, including low‑power sensor networks and power‑constrained device architectures. Hands‑on experience with experimental testing in
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., visualizations, algorithms) in real-time. The MLE will join a dynamic, multi-site team working at the intersection of machine learning, digital phenotyping, pediatric mental health, and real-time clinical decision
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to develop AI-enabled, low-latency signal-processing algorithms for next-generation pixel detectors used in high-energy physics experiments. This position offers the opportunity to engage in cutting-edge
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develop research projects for the Internet of Things for Precision Agriculture (IoT4AG) research grant Develop novel semantic mapping algorithms in the field of agricultural and forestry robotics to promote
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qualified in computer science, mathematics, physics or similar disciplines * Demonstrated expertise in artificial intelligence, machine learning, deep learning, and data mining methods and algorithms Proven
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evaluation of algorithms for early drought stress detection by integrating interactive manipulation strategies with learning-based monitoring methods. This includes designing interaction primitives, processing
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twins, enabling real-time stress-testing under simulated edge cases like cyber-physical attacks and sensor failures. The Research Challenges There exists a complex interplay of factors that present
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for UAV swarm operation. • Develop modular architectures for multi-agent coordination, sensing, and communication. • Integrate sensor suites, flight controllers, and swarm coordination