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Field
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for advanced applications in PET imaging. PET chemistry plays a central role in this endeavor, as the design of radiotracers with optimal in vivo stability, selectivity, and pharmacokinetics is essential
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magnetic response. Development of machine learning methods for exchange-correlation functionals. Current work in the group is focused on improvements and performance optimizations for the recently developed
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chemistry plays a central role in this endeavor, as the design of radiotracers with optimal in vivo stability, selectivity, and pharmacokinetics is essential for generating high‑quality diagnostic images and
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to optimize the design and performance of floating breakwaters. Develop models for stability assessment, structural integrity, and dynamic response of floating systems. 3. Connector Design Design and analyze
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the mentorship of leading experts in one of the following priority research areas: Research area 1: Intelligent Structural Optimization using Physics-Informed Reinforcement Learning Research area 2: AI-Enhanced
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the design, synthesis, and characterization of porous materials to control the release of fertilizers into the soil. The project aims to develop and optimize innovative porous carriers to enhance fertilizer
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, energy system optimization and possibly machine learning to guide energy transitions towards net-zero systems. The research supervisors have prepared multiple potential projects in this area and will work
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optimizing compilers, the classical and quantum fragments are separated in efficient implementations adapted to the changing QPUs and GPUs architectures. The candidate will work at the intersection
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of modular floating structures. Optimize designs for dynamic environmental conditions (e.g., waves, tides, currents). Finite Element and Structural Modeling: Develop and implement finite element models
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on emerging structure-activity relationships, optimizing compounds so as to advance lead series for proximity inducing modalities (PIM). Solve complex synthesis problems using state-of-the-art methodology