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Field
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to advanced computing resources. The MMD group is responsible for the design and development of numerical algorithms and analysis necessary for simulating and understanding complex, multi-scale systems
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Performance . About You The successful candidate will play a key role in the development and validation of computational tools that integrate spatial transcriptomics, algorithmic methods, and machine learning
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on classical supercomputers. Design and optimize classical simulation algorithms for quantum circuits. Explore approximate classical simulation algorithms (e.g., tensor networks, circuit cutting) to improve
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algorithmic fairness Formulation of new problems and research directions and translating topical issues into algorithmic problems Designing new algorithms and investigating their performance on synthetic and
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development, and computational algorithms A solid understanding of theoretical chemistry and solvation models such as COSMO The ability to work independently as well as collaboratively within a
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resiliency, and energy management algorithm development using MATLAB/Simulink for marine microgrid applications. Knowledge on control is highly preferred. Have experience and commitment to supervising student
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edge-assisted offloading strategies for IoT networks. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is
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classical simulation algorithms for quantum circuits. Explore approximate classical simulation algorithms (e.g., tensor networks, circuit cutting) to improve scalability. Publish scientific papers and present
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research team. Key research areas include: Development of low-carbon materials and tunable thermal energy storage materials integrated with smart sensors and advanced algorithms Creation of Digital Twins
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learning, particularly in deep learning or related areas. No prior knowledge of cryptography is required. Expertise in optimization or efficient algorithm design will be considered an asset. Applications