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Field
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2012, FSPH is fully accredited by CEPH and offers three PhD programs, an MPH with five concentrations, an MHA program, several graduate degrees, and BS degrees in Health Services Management and Public
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one of the following: Econometric methods for causal inference; Data science and machine learning; Survey design and analysis; Qualitative analysis skills specialized in policy and geopolitics A good
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informatics approaches (e.g., machine learning, Bayesian statistics) and spatial data processing and analysis skills would be of advantage. Expertise in Stata, R, or other analytic tools. Strong communication
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of analyzing large-scale population data. Experiences working with electronic health records (desirable). Understanding of clinical informatics approaches (e.g., machine learning, Bayesian statistics) and
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Health, Environmental Health, Biological Sciences, Biostatistics, Data Science, preferably with relevant experience. Prior experience with machine learning is a plus. Recruitment is open immediately and
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understanding of adaptive immune receptor (antibody and T-cell receptor) specificity using high-throughput experimental and computational immunology combined with machine learning. The long-term aim is to
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microphysics, severe storms, and mesoscale meteorology; data assimilation, machine learning, and causal discovery; education and human resources; global biogeochemical cycles and ecosystems; and radiation and
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-FATES model using: Snow cover Flux tower data The idea is to combine established iterative ensemble Kalman methods with novel emerging machine-learning-enabled model calibration techniques recently
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to the work described herein. Qualifications Job Requirements: • PhD in Biostatistics, Bioinformatics, Computational Biology, or other related fields. • Strong foundation in statistical modeling, machine
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Details Title Postdoctoral Fellow in Deep Learning Theory and/or Theoretical Neuroscience School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position