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of morphing drone prototypes by combining structural optimization, lightweight design, and experimental testing. The research assistant will: Participate in CAD/CAE modeling and structural optimization of UAV
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computing and machine learning. The research will emphasize both theoretical advancements and practical implementations optimized for modern HPC systems. The postdoc will primarily contribute to one or more
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optimize composite materials that can significantly enhance the efficiency of wastewater purification processes by leveraging the piezocatalytic phenomenon an emerging technology with great potential
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the innovative use of piezocatalysis. The successful candidate will engage in cutting-edge research to understand, design, and optimize composite materials that can significantly enhance the efficiency
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design. Objectives: The main objective is to support the development and validation of morphing drone prototypes by combining structural optimization, lightweight design, and experimental testing
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computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials. Key duties The successful candidate is expected to: Build and evaluate chemical databases
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experimental projects related to microwave systems, including device testing and optimization. Teaching Responsibilities: Introduction to Semiconductor Physics: Semiconductor materials, band theory, charge
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for polymer-based materials. This project aims to leverage computational chemistry techniques and data-driven approaches to optimize the properties of novel polymer-based materials. Key duties The successful
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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