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-based modeling of hydrological and Earth system processes. The CHAS group conducts world-class research in hydrological and Earth system modeling, large-scale data analytics and machine learning (ML), and
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machine learning algorithms to support the traceability of the beef’s geographical origin. She/he will participate in all stages of the project, including planning and supervision of sample collection and
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, observations, a hierarchy of numerical models, and machine-learning methods to understand their formation, dynamics, and predictability. The successful candidate will have substantial freedom to develop
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National Energy Technology Laboratory (NETL) | Albany, New York | United States | about 15 hours ago
, are considered. The participant will gain experience in multi-scale computational modeling and machine learning of mechanical behavior of high temperature alloys. They will be a part of interdisciplinary team and
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desirable. Experience with artificial intelligence, machine learning, reinforcement learning, or optimization techniques applied to autonomous systems is considered an asset. Proficiency in relevant
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shape an ambitious research programme at the intersection of computer vision, machine learning, and foundation models. Research Focus The project investigates how visual foundation models can efficiently
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development About You You will hold a Ph.D/D.Phil in a quantitative or theoretical discipline (e.g. machine learning, computer science, mathematics, statistics, physics, theoretical neuroscience or a closely
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image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial intelligence models would be advantageous What We Offer The appointee would be exposed to ample
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with training and using protein language models or similar experience with non-protein large language models. Expertise in python and machine learning implementations (e.g., pytorch). Expertise in other
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and assessing weld quality of mechanical parts in real-time by developing machine learning models that use sensor data and other tasks that are assigned to you. Core Responsibilities: Understanding