Employment Overview Postdoctoral Positions (available immediately) Focus 1: 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. A PhD in Statistics or a closely related field is required. Experience in programming and manipulation of large datasets is required. Focus 2: environmental modeling, functional data and space-time data analysis. In collaboration with other research groups, 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. Applicants should have experience in applications of statistics to atmospheric or oceanic science. A PhD in Statistics, or a PhD in Geosciences with a strong statistical background is required. Strong collaborative skills are highly desirable. Focus 3: machine learning and deep learning for spatio-temporal statistics. The research projects are in the intersection between spatio-temporal statistics and machine learning. Applicants should have experience in machine learning and deep learning algorithms and programming. Other related projects include developing advanced data-driven methods for cybersecurity and anomaly detection. Applicants should have experience in applications of statistics to atmospheric or oceanic science. A PhD in Statistics, or a PhD in Geosciences with a strong statistical background is required. Strong collaborative skills are highly desirable. Duration: postdoctoral appointments are renewablel annually with an expected duration of 2-3 years. Salary: The positions come with a highly competitive tax-free salary as well as free housing and free health/dental insurance among other excellent benefits. To apply: email a CV, statement of research interests, and names and contact information for at least two references to Prof. Ying Sun (http://es.kaust.edu.sa) at ying.sun@kaust.edu.sa About KAUST: King Abdullah University of Science and Technology (KAUST; http://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's most pressing challenges related to water, food and energy sustainability as well as their impact on the environment. Statistics (http://stat.kaust.edu.sa) is within the Computer, Electrical, and Mathematical Sciences and Engineering Division.
