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Overview
About the project
Scientific machine learning (SML) is an emerging field focused on leveraging machine learning across different sciences whose natural processes are governed by well-established physical equations. Early successes have been reported by the geophysical community in terms of modelling various wave phenomena by means of PINNS, e.g. eikonal equation (bin Waheed et al., 2021) and wave equation (Alkhalifah et al., 2021). Alternative solutions have recently emerged in the SML community with the aim of overcoming some of the limitations of PINNs and extending applicability from functionals to operators.
This Learning to Model Geophysical Processes With NNS (Internship) project offered at King Abdullah University of Science and Technology (KAUST) will investigate such approaches in the context of geophysical modelling and inversion and identify the benefits and limitations when compared to traditional modelling methods as well as PINNs. References: - U. bin Waheed, E. Haghighat, T. Alkhalifah, C Song, Q Hao, 2021, PINNeik: Eikonal solution using physics-informed neural networks, Computers & Geosciences. - T. Alkhalifah, C. Song, U. Waheed, Q. Hao, 2021, Wavefield solutions from machine learned functions, arXiv preprint arXiv:2106.01433.
Get more details
Visit programme websiteProgramme Structure
The candidate will be tasked with:
- Literature review of ML methods for learning physical phenomena governed by PDEs.
- Develop and implement one of the methods for a geophysical PDE of choice.
- Compare pros and cons of the developed method against state-of-t
Check out the full curriculum
Visit programme websiteKey information
Duration
- Part-time
- 3 months
Start dates & application deadlines
You can apply for and start this programme anytime.
More details
Students can choose their own start and end dates as the program runs across the year
Language
English
TOEFL® IBT 79
Delivered
On Campus
Disciplines
Earth Sciences Engineering Management View 7 other Short Courses in Earth Sciences in Saudi ArabiaExplore more key information
Visit programme websiteAcademic requirements
GPA 3.5
English requirements
TOEFL® IBT 79
Student insurance
Make sure to cover your health, travel, and stay while studying abroad. Even global coverages can miss important items, so make sure your student insurance ticks all the following:
- Additional medical costs (i.e. dental)
- Repatriation, if something happens to you or your family
- Liability
- Home contents and baggage
- Accidents
- Legal aid
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Remember, countries and universities may have specific insurance requirements. To learn more about how student insurance work at King Abdullah University of Science and Technology (KAUST) and/or in Saudi Arabia, please visit Student Insurance Portal.
Other requirements
General requirements
- Official Transcript(s) in English from current and previous institutions
- Letter of Recommendation from faculty member in field of study
- Valid Passport(with six months validity)
- CV - Summary of your career, qualifications and education.
- Statement of Purpose-Explain your motivation to become a VSRP intern
Make sure you meet all requirements
Visit programme websiteTuition Fee
To always see correct tuition fees
-
International
FreeTuition FeeBased on the tuition of 0 SAR per year during 3 months. -
National
FreeTuition FeeBased on the tuition of 0 SAR per year during 3 months.
This is a fully-funded internship; it includes tuition, airfare, housing, medical insurance, visa reimbursement and a monthly stipend of $1,000.
Living costs for Thuwal
2270 - 3445 SAR /month
Living costs
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Funding
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