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Harvard Data Science Postdoctoral Fellows

Harvard Data Science Postdoctoral Fellows

January 19, 2017

The Harvard University Data Science Initiative is seeking applications for its inaugural Harvard Data Science Postdoctoral Fellows Program for the 2017-2018 academic year. The normal duration of the Fellowship is two years. Fellows will receive a generous salary as well as an annual allocation for research and travel expenses. A focus of this program is on methodological foundations, including most of statistics. More information is available here.

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Recent Faculty E-prints on arXiv

Anytime Monte Carlo
Lawrence M. Murray, Sumeetpal Singh, Pierre E. Jacob, Anthony Lee

A Divide and Conquer Strategy for High Dimensional Bayesian Factor Models
Gautam Sabnis, Debdeep Pati, Barbara Engelhardt, Natesh Pillai

Advances in using Internet searches to track dengue
Shihao Yang, S. C. Kou, Fred Lu, John S. Brownstein, Nicholas Brooke, Mauricio Santillana

Rgbp: An R Package for Gaussian, Poisson, and Binomial Random Effects Models with Frequency Coverage Evaluations
Hyungsuk Tak, Joseph Kelly, Carl N. Morris

Robust Variable and Interaction Selection for High-Dimensional Classification via Logistic Regression
Yang Li, Jun S. Liu

Sparse Sliced Inverse Regression for High Dimensional Data
Qian Lin, Zhigen Zhao, Jun S. Liu

SLANTS: Sequential Adaptive Nonlinear Modeling of Vector Time Series
Qiuyi Han, Jie Ding, Edoardo Airoldi, Vahid Tarokh

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Recent Faculty Books

Handbook of Statistical Methods and Analyses in Sports
ed. Jim Albert, Mark Glickman, Tim Swartz, Ruud Koning

Unobserved Components and Time Series Econometrics
ed. Siem Jan Koopman, Neil Shephard

Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
Guido Imbens, Donald Rubin

Handbook of Mixed Membership Models and Their Applications
ed. Edo Airoldi, David Blei, Elena Erosheva, Stephen Fienberg

Introduction to Probability
Joseph Blitzstein, Jessica Hwang (Harvard Statistics AB/AM alumnus)

An Introduction to Quantitative Finance
Stephen Blyth

Strength in Numbers: The Rising of Academic Statistics Departments in the U.S
ed. Alan Agresti, Xiao-Li Meng

Designs for Clinical Trials
ed. David Harrington

Handbook of Markov Chain Monte Carlo
ed. Steve Brooks, Andrew Gelman, Galin Jones, Xiao-Li Meng