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thermal and/or thermochemical energy storage systems. Implementing and validating advanced thermodynamic models for performance prediction and optimization. Collaborating with experimentalists and industry
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methods to improve prediction model generalizability, model fairness, and generalizability of fairness across different clinical sites. The researcher will have the opportunity to use machine learning and
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/or high-temperature heat pumps based on power cycles. Design thermal and/or thermochemical energy storage systems. Implementing and validating advanced thermodynamic models for performance prediction
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evaluation methods for vision models Design metrics to compare neural and behavioral data with computational predictions Collaborate with CRC groups on open, reproducible standards for model evaluation Mentor
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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group (https://bckrlab.org). We focus on high impact applications and work on knowledge-centric AI and biomedical machine learning including multi-omics integration, single cell analysis, and sequential
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
, and Precision Health. The project aims to leverage AI and machine learning (ML) to analyze complex metabolomics datasets and address key health challenges, including biomarker discovery, disease
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 18 hours ago
predictive modeling and pathfinding. This includes exploring the use of large language models (LLMs) for schema mapping and normalization tasks, evaluating embedding strategies that enhance interpretability
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physics, applied mathematics, machine learning, bioinformatics, biophysics, spectroscopy, image processing, ecological modeling, molecular biology, plant physiology, marine biology or an interest in gaining