Senior Researcher, Machine Learning

4 days ago

London, United Kingdom MBN Solutions Full time €60,000

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 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

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
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

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