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Field
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accurate completion. Algorithm Design: Design and implement algorithms for tensor completion, considering the unique challenges posed by sparse and multidimensional network data. This involves developing
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. Within this field, we are continuously developing and adopting various algorithms for multiple applications such as automating quality control, detecting process deviations and finally predicting
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and Electronics group in the Electrification Section of EEID/ ESTD, at Oak Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Develop and deploy algorithmic tools for monitoring
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aimed at breakthrough innovations in model capabilities, reasoning, safety, and efficiency. Algorithm & Model Development (LLMs & AIGC): Design and develop novel architectures for large-scale language and
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cooperative, competitive, and mixed settings. Collaborative decision-making frameworks and decentralized learning algorithms. Adaptive, meta-learning, and context-aware strategies to enhance policy
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Description The Quantum Information team at UMass Amherst is involved with modeling and optimization of quantum hardware, as well as development of new modeling methods and algorithms, in collaboration with
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patient records exploiting HPC, including GPUs embedded within NHS infrastructure. Development and deployment of ML operations software and tooling for ML / LLM algorithms working over free-text clinical
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collection methods for external data (e.g. web scraping) to collect data for use in modelling and analysis. Develop analytic plans, engineer supporting algorithms, write new functions or applications in
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include: Advanced Reinforcement Learning: From sample-efficient offline RL to multi-agent coordination and hierarchical RL, we are developing algorithms that can learn complex behaviors and strategies in
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at the interface between computational design and in vitro experiments, the team has developed multiple in silico and in vitro methods to design novel antibodies and nanobodies as therapeutic agents and research