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Ansök senast: 2025-03-04
MBN Solutions | Senior Researcher - Physics Informed ML
Publicerad 2025-01-03
Senior Researcher - Physics Informed Machine Learning
1 day per week in the office outside of London - could be less if required
Up to £60,000 + bonus
MBN Solutions have been retained by our client who are well respected in the field of research to help them bring on board a Senior Researcher specialising in Physics Informed Machine Learning.
You will be working on exploring how to use Machine Learning in Scientific Computing related applications and we have a strong preference for the development of AI techniques that can be applied in the real world and that directly contributeto social good.
The Job:
- The development of new state-of-the-art of physics-informed machine learning techniques focused on atomistic simulation of molecules and materials
- Implementation of these techniques into proof-of-concept code and demonstrations that can be used to present our innovation to internal and external stakeholders and get their feedback
- Monitoring the wider area of physics-informed machine learning in order to be up to date with advances in other fields such as computational fluid dynamics or weather prediction
- Acquiring domain specific knowledge in target application areas, that will enable you to both communicate with people in that field and to develop AI methods that can contribute to it
- Generating IP and publishing work in top academic conferences and journals
The Person:
- Pro-active in your approach, adaptable and able to demonstrate that you have experience with applying physics-informed machine learning techniques for surrogate modelling for atomistic simulations, such as machine-learning force fields
- High proficiency in one or more programming languages(Python preferred) and experience with one or more Deep Learning framework (PyTorch preferred)
- A track record of writing academic publications
- Excellent written and verbal communication skills
- Experience with high-performance computing (HPC) or parallel computing
- Application of physics informed machine learning for other scientific computing fields such as computational fluid dynamics, structural analysis or weather modelling
- Experience with scientific computing and numerical methods for simulation
Fler jobb från Talent
2025-01-03
2025-01-03
2025-01-03