Advanced PhD Researcher in Hybrid Simulation Methods
4 days ago
**Job Overview**
The University of Cambridge is seeking a highly motivated PhD researcher to contribute to an exciting project exploring hybrid simulation methods that combine machine learning with classical simulation technologies. This cutting-edge approach aims to establish a new standard in computational performance.
**Estimated Salary:** £25,000 - £30,000 per annum (dependent on experience)
**Job Description:** The successful candidate will investigate the integration of Neural Operators-efficient learning-based partial differential equation (PDE) solvers defined on simplified domains with domain decomposition strategies. This role requires expertise in advanced computational methods, machine learning techniques, and collaboration within a multidisciplinary team based at the University of Cambridge and Siemens Digital Industry Software.
**Required Skills and Qualifications:*
- Bachelor's or Master's degree (preferably a first or its equivalent) in Engineering, Machine Learning, Applied Mathematics, or related fields.
- Strong background in computer-aided engineering and simulation methods.
- Experience with Python programming and neural networks.
**Benefits:** The University actively supports equality, diversity, and inclusion and encourages applications from all sections of society. Additionally, the successful candidate will have opportunities for professional development, networking, and access to state-of-the-art research facilities.
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Cambridge, Cambridgeshire, United Kingdom University of Cambridge Full time**About the Project**This PhD research project focuses on developing innovative hybrid technologies that merge machine learning and classical simulation techniques to enhance computational speed and accuracy. As part of this project, you will explore the application of Neural Operators for efficient learning-based PDE solvers on simplified domains, combined...
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