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Field
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Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your
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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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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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-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
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and apply AI and machine learning methods for signal processing, image analysis, data fusion, and prediction; · build physics-informed and hybrid AI models that combine geophysical knowledge with data
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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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demonstrate exceptional skills and experience relevant to the role. Applications are invited for the post of Postdoctoral Research Associate in Applied Machine Learning for High-Stakes Regulated Domains in
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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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field of research Participate in education, and PhD and master student supervision Profile Strong background in computational biology, bioinformatics, machine learning, or a related quantitative field