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, proteomics, metabolomics) and artificial intelligence/machine learning (AI/ML) applications in biomedical research will be considered a strong advantage. Outstanding U of A benefits include health, dental
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, registry data, health data, laboratory data, electronic health records, biomedical informatics standards. Working kowledge or direct experience in SCN8A-related disorders. Experience in machine learning
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-doctoral Associate will develop algorithms and theory for machine learning methods, as well as implement and apply ML methods to problems in domains such as computational biology and neuroscience. This is a
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nuclear physics detectors. Experience analyzing data from high energy or nuclear physics experiments. Familiarity with Monte Carlo simulations. Familiarity with machine learning techniques. About the
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disease-causing organisms. Outstanding U of A benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; U of A/ASU/NAU tuition reduction for the employee and
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the application of machine learning techniques (e.g., doc2vec, encoder models, multi-modal embeddings, large language models) to map concepts and their relationships, tracing how they change, merge, or diverge
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Experience with super-resolution ultrasound, US localization microscopy, photoacoustic imaging, elasticity imaging, pulse encoding, solving inverse problems, machine learning, AI, SolidWorks, 3D printing FLSA
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machine learning analyses will be performed to determine correlations across stimulation settings and body systems as well as to develop predictive models and biomarkers for physiological and clinical
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equitable scholarly environment in research, mentoring, and service. Your work will focus on the SEAMLESS (SEmi-Automated Machine LEarning Search for Semi-resolved galaxies) survey, whose goal is to identify
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demonstrated experience with a set of tools appropriate for working with large-scale data science including application of machine learning. In addition, applicants must have demonstrated leadership experience