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Are you inspired by the quest for new materials for solar cells, spintronics, and quantum technologies—and eager to accelerate their discovery with machine learning and materials theory? Are you
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 4 hours ago
prediction using large-scale multimodal neuroimaging data. The research will emphasize methodological innovation in statistical modeling, transfer learning, machine learning, model ensemble strategies, and
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Postdoctoral researcher in marine ecosystems modelling for the Marine and Continental Waters Program
of machine learning and AI algorithms and methods. Knowledge of species distribution models. Catalan and Spanish are valued LanguagesENGLISHLevelGood Research FieldOtherYears of Research Experience1 - 4
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Geospatial analysis, machine learning, and predictive modelling, Have a good command of programming tools such as R packages, Phyton, and other programming languages Publications in the field Excellent
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and radar remote sensing, climate time series, and hydrological models. The work will employ machine learning and explainable AI techniques to improve flood prediction under different hydroclimatic
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related field. Documented expertise in machine learning and time-series modelling (e.g. LSTM, XGBoost, CNN). Strong programming skills in languages such as Python and R. Experience with phenotyping data
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, statistics, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology
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analytical models Physics-informed machine learning for deformation modeling and prediction Integration of perception, planning, and control for robust real-time robotic performance Requirements Ph.D. in
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(HR+/HER2-) and aims to develop predictive models of therapeutic response using machine learning combined with Fourier-Transform Infrared Spectroscopy (FTIR) applied to blood, saliva, and tumor tissue
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presentation of analysis results. The ability to work with large and complex datasets. Excellent spoken and written English skills. Experience in machine learning, predictive modeling, and/or Bayesian methods