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- Tasks: Develop cutting-edge physics-informed ML techniques for atomistic simulations and present innovations.
- Company: Join a respected research firm focused on impactful scientific computing applications.
- Benefits: Enjoy flexible work arrangements, competitive salary, and bonus opportunities.
- Why this job: Make a real-world impact with AI while collaborating with experts in a dynamic environment.
- Qualifications: Experience in physics-informed ML, programming (Python preferred), and strong communication skills required.
- Other info: Opportunity to publish in top academic journals and conferences.
The predicted salary is between 43200 - 72000 £ per year.
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
Senior Researcher - Physics Informed ML employer: MBN Solutions
Contact Detail:
MBN Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Researcher - Physics Informed ML
✨Tip Number 1
Make sure to showcase your experience with physics-informed machine learning techniques in your conversations. Highlight specific projects where you've applied these methods, especially in atomistic simulations, as this will resonate well with our team's focus.
✨Tip Number 2
Stay updated on the latest advancements in related fields like computational fluid dynamics or weather prediction. Being able to discuss recent developments will demonstrate your proactive approach and genuine interest in the domain.
✨Tip Number 3
Prepare to discuss your programming skills, particularly in Python and any deep learning frameworks like PyTorch. Be ready to share examples of how you've used these tools in past projects, as technical proficiency is key for this role.
✨Tip Number 4
If you have published academic work, be prepared to talk about it. Discussing your contributions to top conferences and journals will not only highlight your expertise but also show your commitment to advancing the field.
We think you need these skills to ace Senior Researcher - Physics Informed ML
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with physics-informed machine learning techniques, programming skills (especially in Python), and any relevant academic publications. Emphasize your adaptability and pro-active approach.
Craft a Strong Cover Letter: In your cover letter, express your passion for applying machine learning to scientific computing. Mention specific projects or experiences that demonstrate your expertise in the field and how they align with the company's goals of contributing to social good.
Showcase Your Research Experience: Detail your experience with high-performance computing and any relevant projects involving atomistic simulations or other scientific computing fields. Highlight your track record of publishing in top academic conferences and journals.
Prepare for Technical Questions: Be ready to discuss your knowledge of deep learning frameworks like PyTorch and your experience with numerical methods for simulation. Prepare examples of how you've implemented machine learning techniques in real-world applications.
How to prepare for a job interview at MBN Solutions
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with physics-informed machine learning techniques in detail. Highlight specific projects where you've applied these methods, especially in atomistic simulations or surrogate modeling.
✨Demonstrate Your Programming Skills
Since proficiency in programming languages like Python is crucial, be ready to talk about your coding experience. You might even be asked to solve a problem on the spot, so brush up on your skills with relevant frameworks like PyTorch.
✨Communicate Effectively
Excellent written and verbal communication skills are essential for this role. Practice explaining complex concepts in simple terms, as you may need to present your ideas to stakeholders from various backgrounds.
✨Stay Updated on Industry Trends
Research the latest advancements in physics-informed machine learning and related fields such as computational fluid dynamics. Being knowledgeable about current trends will show your passion and commitment to the field.
