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materials. * You have familiarity with artificial intelligence (AI) and machine learning (ML) methodologies and interested in advancing these tools for accelerating the analysis of the big data acquired by
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closely with data scientists to interpret and predict MFA data using nonlinear reaction-diffusion models, 13C-isotopomer analysis, and MATLAB-based simulations enhanced by Bayesian Machine Learning
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analysis, and MATLAB-based simulations enhanced by Bayesian Machine Learning. The ideal candidate should have a strong background in cell culture, and lipid metabolism, with experience in mass spectrometry
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, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu
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interest in the use of machine learning techniques to enable new analysis strategies, as well as the application of deep understanding of the detector to enable novel physics studies. The group also has a
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for 2 years. You will lead a research team working on the application of software (AI/machine learning techniques), to improve the efficiency of advanced hardware and integrated circuit design. This role
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, enhanced by machine-learning and data-driven analysis techniques. Additionally, the study will encompass electrically triggered events that mimic the voltage-based signaling of biological synapses
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in the University of Minnesota. The research will focus on applying, developing and implementing novel statistical methods for causal inference, integrative data analysis or/and machine/deep learning
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, fixed term period for 2 years. This role will help establish a research programme in statistical, data-science, and/or machine-learning approaches to stellar and exoplanetary physics, broadly interpreted
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, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment