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computing, and digital twin technologies for mission autonomy and predictive analytics. The research assistant will develop real-time flight control algorithms, AI- based data processing, and mission
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. Development of real-time optimization algorithms and model predictive control (MPC) strategies for adaptive process management. Addressing data sparsity and data quality issues in industrial process data
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. We propose the integration of randomized algorithms into sparse optimization frameworks for the purpose of completing multidimensional networks by studying the theoretical foundations behind randomized
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to join our cutting-edge team, working on the development of advanced AI/ML algorithms for battery management systems (BMS) in electric mobility and micro mobility applications. The primary focus will be
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to develop algorithms and methodologies for mapping irrigation patterns using satellite imagery. Investigate methods for detecting the timing and frequency of irrigation events from time-series remote sensing
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conferences and journals. Overview: The successful candidate will join an interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific
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algorithms in various projects. Contribute to the supervision of doctoral students and interns at the center. Participate in the training courses organized by the center. Work on collaborative projects with
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computing, and digital twin technologies for mission autonomy and predictive analytics. The research assistant will develop real-time flight control algorithms, AI- based data processing, and mission
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using simulation-based parametric studies. Couple computational results with experimental data for model calibration and validation. Apply sensitivity analysis and optimization algorithms to refine model
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Solutions at the UM6P Data Center. Innovate and improve image analysis algorithms for plant trait quantification. Collaborate with international research teams and contribute to joint publications and