Multi-Hazard Modelling Researcher
1 dag geleden
The Department of Applied Earth Sciences at Universiteit Twente seeks a highly skilled researcher to contribute to the development of advanced Physics-Informed Neural Networks (PINNs) for modelling complex interactions between multiple geophysical processes. The successful candidate will have a strong academic background in earth sciences or quantitative sciences, with prior experience in working with mathematical models or neural network architectures.
The primary objective of this Ph.D. position is to create a unified, scalable framework that accurately simulates coupled hazards while addressing computational efficiency and uncertainty quantification. To achieve this, the researcher will investigate feedback mechanisms and energy transfer between hazards, embedding these principles within the network architecture to simulate how an initial hazard evolves into a multi-hazard event.
The ideal candidate will possess excellent programming skills, proficiency in scientific computing, and a solid understanding of uncertainty quantification and remote sensing. They will also be able to work independently and as part of a team, demonstrating enthusiasm for interdisciplinary research and collaboration.
This four-year full-time position comes with a gross monthly salary of € 2,872 - € 3,670, depending on qualifications and experience. The university offers a dynamic ecosystem with enthusiastic colleagues, internationalization being an important part of the strategic agenda. The benefits package includes a professional and personal development program, holiday allowance, year-end bonus, and pension scheme.
Key takeaways include:
- A full-time position for 4 years, with a qualifier after 6-9 months
- A gross monthly salary of € 2,872 - € 3,670
- An inspiring multidisciplinary, international, and academic environment
- Excellent support for research and facilities for professional and personal development
For more information about the position, please visit our homepage. We look forward to receiving applications from talented researchers who are eager to contribute to the advancement of AI on early warning systems.
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Enschede, Overijssel, Nederland Universiteit Twente VoltijdAbout the PositionThe Universiteit Twente is seeking a highly skilled researcher to contribute to the development of advanced Physics-Informed Neural Networks (PINNs) for modeling complex interactions between multiple geophysical processes. The successful candidate will work on a funded PhD position, advancing the scientific field of AI on early warning...
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