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assets include strong programming skills, experience with modern machine-learning techniques such as neural simulation-based inference or transformer architectures, and familiarity with fitting methods and
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the computational task: first-principles active-site descriptor models, high-throughput screening with machine-learned interatomic potentials, and a dedicated catalysis database. This position is ideal for a
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National Energy Technology Laboratory (NETL) | Albany, New York | United States | about 10 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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equations, numerical analysis, mathematicalmodels in biomedicine, biostatistics, machine learning, statistical learning, multivariate statistics, time series,mathematical modelling, generalized linear models
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) develop multimodal machine learning models and methods to determine signatures and biomarkers to understand mechanisms distinguishing spontaneous versus precipitated withdrawal episodes. The spontaneous vs
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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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sensors, RGB/IR cameras, video systems, insect traps, and other devices to build predictive, AI- and machine-learning based models for monitoring grain quality and detecting deterioration due to mold
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WPI-AIMEC established by Tohoku University and JAMSTEC | JP Nagar III Phase, Karnataka | India | 2 months ago
or isotope geochemistry, microbiology/microbial ecology, marine data science (including observational informatics), mathematical and statistical sciences (including AI, machine learning, model development, and
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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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, or foundation models. Familiarity with atomistic simulations (e.g., density functional theory, molecular dynamics). Interest in developing broadly applicable machine-learning methods for physical sciences