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-driven models to optimize solvent systems. Mentoring the training and learning of PhD and undergraduate students on sustainable biomass conversion topics Assist in report/document/further grant writing
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proceedings Collaborate with other researchers on project discussions and joint deliverables Support the preparation of research proposals and grant applications Job requirements: Must hold a PhD degree in
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solid particle transport. The successful candidate will contribute to the creation of an AI-optimized platform capable of achieving up to 50× speedups in simulation performance, enabling real-time, energy
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to etch novel lattice patterns Perform optical characterizations of structures using various optical spectroscopy Collaborate with theoretical researchers in the design and optimization for new fundamental
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/network/circuit patterns Perform characterization of structures using atomic force microscopy and optical spectroscopy Collaborate with theoretical researchers in the design and optimization for new
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uses. To investigate feature-level just-noticeable difference modelling for machines to facilitate assessment and optimization. To formulate a comprehensive visual feature codec for machine uses
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and synthesis of novel materials. Key Responsibilities: Develop and apply generative AI models for materials discovery, leveraging deep learning, Bayesian optimization, and active learning. Integrate
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offers a unique opportunity to drive high-impact research in a collaborative and innovative scientific environment. Key Responsibilities: Contribute to the development and optimization of protein
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into the catalyst and flow processes/ reactor design. Mentor the training of PhD and undergraduate students Assist in report/document/further grant writing Maintenance of lab and computer clusters. Job Requirements
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optimization of these processes to achieve desired material properties and structural characteristics. Key Responsibilities: As part of the candidate's scope of work, they main responsibilities will be focusing