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. Key Responsibilities: Research Excellence: Drive pioneering research in Hydrometallurgy, with a focus on the development of concepts and methodologies that optimize the design and operation of efficient
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, to protect the LFP particles while optimizing their performance in high-energy-density applications. The coated LFP materials should exhibit superior mechanical and chemical resilience, ensuring
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multiplex and multilayer networks alongside with the observed links in order to predict or reconstruct the missing links. The first step is to explore different optimization methods using low rank tensor
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, simulating real operating conditions. Supervise students in experimental projects related to microwave systems, including device testing and optimization. Teaching Responsibilities: Introduction
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-driven modeling, simulation and optimization with strong and permanent interactions with experiments. Integrate artificial intelligence (i.e. machine, deep and reinforcement learning…) to optimize
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(LCC) analyses. These programs should align with the Process Optimization and Sustainability Cluster roadmap, focusing on: Process modeling, simulation, and optimization for chemical, energy, and
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maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance schedules. Publish high-impact research in top-tier conferences and journals
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, and materials characterization to join a cutting-edge research team. The project focuses on developing sustainable and optimized processes for vanadium extraction and purification, with the goal
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platforms). Support modeling, simulation, and data-driven optimization using tools such as ROS, Unity, Modelica, Simulink, and SCADA platforms. Collaborate with faculty and industrial partners to create
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for real-world processes and infrastructures (e.g., factories, greenhouses, robotics platforms). Support modeling, simulation, and data-driven optimization using tools such as ROS, Unity, Modelica, Simulink