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relation with energy generation, CO2 sink building materials synthesis and materials recycling. In the frame of this project, the recruited researcher will specifically work on: (i) the multi-scale
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distributed training, experiment tracking, and MLOps automation. Problem-Solving Skills (15%) – Innovate adaptive fine-tuning, multi-task learning, and agentic reasoning strategies to improve generalization and
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organization for research publications, with potential for co-authorship. Additional details of these responsibilities are provided below: Coordinate the conduct of complex (i.e., multi-drug regimens, high
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]) for healthcare and life sciences. AI Agents and Autonomous Reasoning, including the development of autonomous agents capable of multi-step clinical reasoning and planning, as well as systems that utilize Retrieval
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work on synthesizing multi-source, multi-modal data into a coherent data infrastructure and define the appropriate policies and standards for hosting, managing, and sharing the data typically used
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in advancing research initiatives in health informatics and artificial intelligence, including emerging areas such as agentic AI. In collaboration with faculty and multidisciplinary research teams
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distinguished faculty. For more information about the Department, please visit: https://chemistry.hku.hk. The Position We now invite applications for appointment as Assistant Professor in the following strategic
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and artificial intelligence. This role offers a unique opportunity to support the development and evaluation of a multi-agent Retrieval-Augmented Generation system designed to accelerate understanding
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the United States, and around the globe. The GHRC supports and advances multi-disciplinary large animal and insect vector research, education, and training opportunities for faculty at Texas A&M and their partners
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foundation models and agentic AI models. Experience in large-scale deep learning systems and/or large foundation model, and the ability to train models using GPU/TPU parallelization. Experience in multi