One postdoctoral position is currently available at King Abdullah University of Science and Technology (KAUST) for a collaborative project with a starting date of April 1, 2020. The candidate will be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following areas will be considered when selecting candidates: Machine Learning, Neural Networks, Numerical solutions of Partial Differential Equations and Stochastic Differential Equations, Numerical Optimization, Uncertainty quantification, Approximation Theory, Applied Probability and Bayesian statistics, Optimal Control and Dynamic Programming.
Appointment, salary, and benefits. The appointment period is two years. The salary is highly competitive and no income tax is currently paid to the Kingdom of Saudi Arabia. Benefits include medical and dental insurance, air transportation to KAUST, one round-trip airline ticket per year to visit home country, and free housing while at KAUST (in shared housing unless living with spouse or children).
About KAUST. King Abdullah University of Science and Technology (KAUST) is an international, graduate-level research university, located on the Red Sea near Thuwal, 80 kilometers (50 miles) North of Jeddah, in the Kingdom of Saudi Arabia. Dedicated to inspiring a new age of scientific achievement that will benefit the region and the world, KAUST has the mission of exemplifying the future of world-class research. More details are available at www.kaust.edu.sa.
For more information, see the https://stochastic_numerics.kaust.edu.sa/Pages/Home.aspx
A successful candidate preferably has completed a Ph.D. in the field of applied mathematics or computational engineering, or in any field related to one or more of the areas of research mentioned in the position description. Excellent analytical, computational and programming skills are expected.
Strong interpersonal qualities from the candidate will be appreciated as she/he will be working in a highly collaborative project and will be expected to spend a part of the time at the collaborating institutions.
The positions will remain open until filled, but the candidate is expected to join the team on April 1, 2020, or as soon as possible.