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statistical software & machine learning (e.g., R, Python, SAS, or STATA). Experience working with large population dataset (e.g. EHR, claims data). Background in health informatics, population health research
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
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initiation latency, movement speed, gait characteristics, postural control, motor variability, and other behavioural descriptors. ESSENTIAL REQUIREMENT PhD in machine learning, artificial intelligence
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. Knowledge of survival analysis. Knowledge of machine learning methods. Other Requirements Application materials must include: Curriculum Vitae (CV) Statement of research interests Names of three professional
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or quantitative methods. We are open to a range of methodological backgrounds, including digital trace data analysis, natural language processing, machine learning, experimental design, causal inference, and
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experimental studies, mechanistic modelling, time-resolved data analysis, and machine learning to develop and validate predictive models linking process signals to reaction behaviour, progressing from controlled
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. Successful candidates may come from any relevant discipline. All requirements for the PhD or other terminal degree in the relevant field must be completed by August 1, 2027. A record of publication and
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. Successful candidates may come from any relevant discipline. All requirements for the PhD or other terminal degree in the relevant field must be completed by August 1, 2027. A record of publication and
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meetings, contribute to grant applications, and build an independent research career in cancer immunology and neuro-oncology. Minimum Requirements PhD, MD, MD/PhD, or equivalent doctoral degree in immunology
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-facing web GIS dashboard. Investigate the forest, landscape, and climate conditions that drive storm susceptibility, using major windstorms as natural experiments and interpretable machine-/deep-learning