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security. Expertise in data-driven modeling (ML for energy, forecasting, anomaly detection) and physics-informed learning. Real-time/HIL or embedded control experience (e.g., OPAL-RT, RTDS) and laboratory
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machine learning, deep learning, data visualization, and applied analytics for multi-modal datasets. Technical proficiency with Python, R, SQL, SPSS, Tableau. Architectural and design software expertise
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understanding of the mathematics of neural networks. Prior significant contributions to advanced machine-learning or deep-learning models. Evidence of having led a key research project, indicated by a first
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Type Staff Job Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived
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Type Staff Job Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives, talents & lived
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upon future funding. Qualifications Required Education and Experience Appropriate PhD in a related field. Preferred Qualifications Experience with machine learning and deep neural network techniques
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candidate will work in a multidisciplinary team and have opportunities to mentor graduate students and undergraduate students. Opportunities to Contribute: Numerical model development: Develop coupled models
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College Station, Texas Job Type Staff Job Description Our Commitment Texas A&M University is committed to enriching the learning and working environment by promoting a culture that respects all perspectives
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information here ! PURPOSE We are seeking a highly qualified researcher with a strong interest in applied statistics, machine learning, and artificial intelligence, with a particular focus on time-series
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) years of related work experience. Experience developing machine learning methods. Experience writing, submitting, and editing peer reviewed publications. Expertise in computer science applications