NCAR's Geophysical Statistics Project

Institute for Mathematics Applied to Geosciences Institute for Mathematics Applied to Geosciences

Postdoctoral Opportunities in Statistics at the National Center for Atmospheric Research

Postdoctoral appointments in statistics are a rather new phenomenon and the Geophysical Statistics Project (GSP) is unique among such programs. The quality of young statisticians in our project is extremely high. One strength of GSP is that it gives a new Ph D. the time to develop a solid research program of their own without the other pressures associated with the first few years as a faculty member. In addition, GSP provides a formative environment that encourages the post docs to branch out into new areas and develop applications in the geophysical and environmental sciences. The project is committed to maintaining NCAR connections with the statistics post docs after they leave. Thus, GSP post docs will retain their opportunities for collaboration with scientists here and also have the potential for funding outside the usual Probability and Statistics program at NSF.

Research Projects ... (Collaborating NCAR scientist(s) and division in italics.)

Current GSP post-docs

  • Dorin Drignei, GSP,
    • Quantifying uncertainties in climate system properties Chris Forest, MIT; Bruno Sanso University of California, Santa Cruz
    • Climate change detection and attribution Tom Wigley, NCAR
    • Test for climate similarity Bill Collins, NCAR

  • Tomoko Matsuo, GSP,
    • Data assimilation problems in space weather research; Jeff Anderson, MMM

  • Anders Malmberg, GSP,
    • Space-Time modeling of Atmospheric Carbon Monoxide; Chris Wikle, University of Missouri, Doug Nychka, IMAGe-NCAR, and David Edwards, ACD-NCAR
    • Stochastic transport models

  • Dan Cooley, GSP/Colorado State University,
    • Downscaling of extreme values Naveau, University of Colorado
    • part of the Weather and Climate Impact Initiative.

    ... other GSP members

    • Tim Hoar
      • Computational, Geophysical support for the Geophysical Statistics Project
      • Data Assimilation Jeff Anderson, Kevin Raeder, Hui Liu
      • Analysis of remotely-sensed oceanic winds Ralph Milliff Colorado Research Associates; Rol Madden CGD

    • Doug Nychka
      • Spatial Statistics for large datasets
      • Asymptotic theory for spatial process estimates.

    • Steve Sain, CU-Denver,
      • Crop modeling, weather generators
      • Sarah Streett, Uli Schneider

    Last modified: Jan 25 2005   by thoar "at" ucar "dot" edu