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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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rate standardization, stock assessment models, and statistical modeling in both frequentist and Bayesian frameworks • A solid track record of publications Salary Information Commensuate with experience
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of this position will be development of custom neural networks for functional annotation of protein sequences. This is an Extended Temporary Employment (ETE) position. Outstanding UA benefits include health, dental
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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
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experience in developing models to analyze temporal data. Prior experience in utilizing Bayesian modeling in related applications. Required Application Materials: CV Contact information for reference letters
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Arctic locations- Knowledge of spatial analysis and Bayesian statistics - Previous experience conducting fieldwork in northern ecosystems - Experience working with drone imagery and drone piloting Offer
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. This position offers an exciting opportunity to work at the intersection of HPC and AI, addressing critical communication bottlenecks and optimizing network interconnects for large-scale distributed systems
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are formed in bone-conduction. We perform intracochlear measurements of sound pressures and vibrations in human cadaveric ears. We develop circuit network models and finite element models to assist data
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systems and wireless communication. Positioned at the intersection of these two areas and within the Division of Secure and Networked Systems, this position offers an opportunity to work on integrating
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. amino acid and lipid metabolism), signaling pathways (e.g. mTOR and nutrient signaling), and systems-level regulatory networks that regulate basic T cell and dendritic cell biology and antitumor immunity