How do I know who my advisor is? Can I change my advisor?

​For M.S. students, your advisor when you are admitted to KAUST is the Program Chair. For Ph.D. students, your advisor is your PI (supervisor) whose lab you have been accepted in to. 

Yes, you can change your advisor. M.S. students are advised to do so if/when they begin their thesis or directed research.  Ph.D. students do have the ability to change advisors, but the overall impact to the Ph.D. project, as well as the time left to finish the Ph.D., could be significant.  This will have to be taken into account before approval.

​M.S. students need 36 credits (combination of courses and research is specific to your program). 

Ph.D. students need 6 credits of 300-level coursework and will earn dissertation research credit each semester until they defend (no minimum credits established, although there is a minimum residency requirement of 2.5 years).

​During your final M.S. semester at KAUST, you will be eligible to submit a “rollover” application.  You will be contacted by the Admissions Office for this.  You must have a confirmed supervisor in order for the application to be approved.

​M.S. students get all university holidays (Eid Al-Fitr, Eid Al-Adha, Spring break).  

Ph.D. students get university holidays and three weeks of annual/vacation leave per calendar year to be taken in agreement with your PI.

​Mandatory, core and elective courses are listed in the program guide. The program guides for all BESE programs can be found here 
​“Time Extension to Complete M.S. Thesis” application request can be submitted by the 9th week of your final Fall semester.  See application for required approvals here .
​No.  Only once during your time here at KAUST.  If “WE Courses” appears on your KAUST transcript, that means you have met this requirement.​
​Yes, both M.S. and Ph.D. in all BESE programs must register, attend, and receive an S grade for the graduate seminar each semester (Spring and Fall, NOT summer).

​Yes. Drop and Add deadlines are on the academic calendar.

​Your GPC can help you request these from the Registrar’s Office, or you can contact them directly at  RegistrarHelpDesk@KAUST.EDU.SA​​ 

Latest Events

How to present scientific data - Making nice graphics, analyzing and presenting your data well

Making nice graphics and analyzing and presenting your data well

It can never be stressed enough that the figures (graphics) in your report or scientific paper are the first thing that everyone looks at. They must be of very good visual quality, presenting your data in a clear and insightful manner. This will help your readers to appreciate your report or paper more and give it more attention and thus it will have more impact. Of special importance is the topic of “error bars” and everything related to that. In the presentation we illustrate how you help yourself if you try to avoid error bars, but instead simply present all data. Also your life in the lab can be more pleasant if you follow some simple advises related to how you will later on present your data. 

Before the break we look at making nice and elegant graphics that help to make your data are presented in the best way without fancy statistics. After the break we go into some specific examples of what is sometimes hidden behind error bars and ‘box and whisker’-plots. We also discuss how to present values in tables.

Dr. Maarten Biesheuvel is principal scientist at Wetsus, European Centre for Sustainable Water Technology, The Netherlands. He is the author of two textbooks on electrochemical processes and 160 scientific publications in the field of the theory of transport processes and physical chemistry, including theory for capacitive deionization, electrodialysis, and reverse osmosis. He is in editorial board member of the journals Desalination and J. Membrane Science Letters. He is regularly invited to give tutorial lectures on transport theory and chemical equilibrium, specifically on reverse osmosis and electrodialysis, as well as on the history of theory for activity coefficients of ions. Other highly acclaimed tutorial lectures provide students (BSc to PhD level) with useful insights in data analysis and graphical presentations of data.


Dr. Maarten Biesheuvel