[Statlist] 3 POSTDOC POSITIONS IN STATISTICS AT KAUST

[Marc G. Genton]

King Abdullah University of Science and Technology (KAUST; www.kaust.edu.sa) is an international, graduate research university dedicated to advancing science and technology through interdisciplinary research, education, and innovation. Located in Saudi Arabia, on the western shores of the Red Sea, KAUST offers superb research facilities together with unmatched living conditions for individuals and families. The generous social policy coupled to the top-quality research facilities have succeeded in attracting top international faculty, scientists, engineers, postdocs and students. KAUST�s fundamental goal-oriented and curiosity-driven research is employed to address the world most pressing challenges related to water, food and energy sustainability as well as their impact on the environment.

Statistics (stat.kaust.edu.sa) is within the Computer, Electrical, and Mathematical Sciences and Engineering Division, and part of the program on Applied Mathematics and Computational Science. The following 3 postdoc positions are available:

[1] One postdoc position in the group of Prof. Marc G. Genton (stsda.kaust.edu.sa) to work on a new project on space-time statistical models for wind field forecasting with climate model output and high performance computing. The project is joint with the National Center for Atmospheric Research (NCAR) in Boulder, Colorado, and with Newcastle University in the UK. This postdoc is expected to visit these two institutions for joint research. Expertise in at least two of the following areas is necessary: spatial and spatio-temporal statistics; processes on spheres; multivariate computational statistics; massive datasets; parallel computing; emulators.

[2] One postdoc position in the group of Prof. Ying Sun (es.kaust.edu.sa) to work on computational challenges in working with large spatial-temporal datasets with applications to climatology and meteorology among other areas. Specific possible projects include computation of exact and approximate likelihoods for Gaussian processes with unstructured covariance matrices, non-Gaussian process models for spatial-temporal data and spectral methods for nonstationary processes. Applicants should have experience in applications of statistics or computational mathematics to the physical sciences. Experience with manipulation of large datasets is required.

[3] One postdoc position in the group of Prof. Ying Sun (es.kaust.edu.sa) to work on environmental modeling, functional data and space-time data analysis. In collaboration with research centers, we are particularly interested in statistical models and methods for problems in hydrology, plant science, marine science and ecology. Potential research topics include: spatio-temporal modeling of environmental problems, and characterization and comparison of space-time variability in various data products.

The successful candidates will have a doctoral degree in Statistics or relevant to the projects. Experience in interdisciplinary research is desirable and excellent programming skills are necessary.

Desired starting date for these positions is April 1, 2016, but earlier or later times can be arranged. Postdoctoral appointments are renewable annually. The expected duration is two years.

To apply, email a CV, statement of research interests, and names and contact information for two references to Marc G. Genton (marc.genton using kaust.edu.sa) for position [1] or to Ying Sun (ying.sun using kaust.edu.sa) for positions [2] and [3]. Applications are accepted until January 31, 2016 or until the positions are filled.




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