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working at the University of Arizona and relocations services, please click here . Duties & Responsibilities Develop novel ML / AI models and techniques for analysis of longitudinal time series data
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. Mathematical techniques include qualitative and numerical analysis of deterministic and stochastic dynamical systems, optimal control, network models, and machine learning. Preference will be given to candidates
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algorithms, environmental time series and anomaly detection. SALARY: Up to $6,250.00 Monthly ($75,000.00 Annual, Approximately) NOTE This is a grant funded position with continued employment contingent upon
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the guidance of the PI. Travels to scientific conferences to give presentations. Attend weekly Medical Physiology Seminar Series and meet with guest lectures Utilizes summarized results in scientific and/or
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the long-standing and counterintuitive observation of attraction between similarly charged particles in solution. In a series of papers we described the mechanism behind an “electrosolvation force” that can
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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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of attraction between similarly charged particles in solution. In a series of papers we described the mechanism behind an “electrosolvation force” that can drive such an attraction (J Chem Phys 2020, Langmuir
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manufacturing challenges. The AMMIC team will be undertaking a series of projects with industrial collaborators in the areas of: Materials synthesis (e.g. PVD techniques, Metamaterials, etc.); Digitalisation
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our expertise in bioinformatics and metagenomic analysis we offer hands-on clinical experience through cohort studies. These include cross-sectional and longitudinal cohorts, time-series intervention
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. Beyond our expertise in bioinformatics and metagenomic analysis we offer hands-on clinical experience through cohort studies. These include cross-sectional and longitudinal cohorts, time-series