[Statlist] 10 VACANCIES FOR PH.D. STUDENTS IN STATISTICS AT KAUST, AVAILABLE NOW

[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 (AMCS). The following Ph.D. or M.S./Ph.D. student positions are available in the Statistics groups:

[1] Four student positions are available in the group of Prof. Marc G. Genton (stsda.kaust.edu.sa) to work on research  projects related to spatial and spatio-temporal statistics, computational statistics, massive datasets, and parallel computing, with applications mainly in environmental sciences and renewable energies.

[2] Two student positions are available in the group of Prof. Raphael Huser (extstat.kaust.edu.sa) to work on research  projects related to the development of models and efficient inference methods for extreme events recorded in space and/or time, such as floods, heat waves or wind gusts, and applications of Statistics of Extremes to large data problems.

[3] Four student positions are available in the group of Prof. Ying Sun (es.kaust.edu.sa) to work on research  projects related to visualization, modeling, computations and applications for space-time data and functional data, with applications to environmental sciences and engineering, including climatology, meteorology, hydrology, plant science, marine science and ecology.


Candidates should have a strong background in statistics, data science, applied mathematics,
or a related field, and good programming skills (e.g., R, or Matlab, C++).

KAUST offers the assistance of highly qualified faculty members, top
computational facilities and resources, a very nice campus located by the
Red Sea with a multicultural community (with more than 100 nationalities
represented on campus), and highly competitive compensations and benefits.

APPLY HERE by January 1, 2016 for Fall 2016 admission (select AMCS program, Statistics specialization):
http://www.kaust.edu.sa/application-form-kaust.html



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