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Field
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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
images, including Positron Emission Tomography, temporal multi-modal MRI and Histology, which we use for models training and validation. Objectives A key research focus of our group is the optimization
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to an ongoing project on the design and manufacturing of adaptive winglets using Shape Memory Alloys (SMAs) for aerospace applications. These smart winglets are designed to optimize aerodynamic performance by
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and reinforcement learning for real-time optimization, fault self-recovery, and production scheduling in industrial processes. Publish research results in top-tier international conferences and journals
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theoretical foundation. We are looking for a candidate excited by the challenge of rethinking data systems in the face of modern constraints such as optimization under uncertainty, constrained query evaluation
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use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities are experimentally driven and
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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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from estimation and optimization theory to hardware design. The specific topic of the project falls in the intersection of statistical signal processing and applied mathematics and is in particular
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to understand mechanisms for impurity removal (e.g., Cu, Al, Fe) and for better recovery of Co, Ni, and Mn. Identify and optimize key process parameters for black mass treatment in close collaboration with
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the optimization process. This project will play a key role in translating advanced CFD–ML methodologies into practical design and control strategies, helping unlock the full potential of urban wind energy
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structures, integrating morphing wings and additive manufacturing processes for high-performance and energy-efficient drones. Keywords: Morphing wings, composites, additive manufacturing, aerodynamics, UAV