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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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will include: Establishing and optimizing cell culture protocols under sterile conditions (adherent or suspension eukaryotic cell lines). Designing, establishing protocols and conducting recombinant
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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 structural analysis Cheminformatics and chemical data mining Computational catalysis or process optimization AI applications in analytical, organic, inorganic, or physical chemistry Automation in
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proteins. Under the supervision of the project leader, your responsibilities will include: Establishing and optimizing cell culture protocols under sterile conditions (adherent or suspension eukaryotic cell
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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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experts to integrate LLM-based solutions into predictive maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance schedules. Publish high
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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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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