In this episode, Neil Ashton explains his move to Mistral as VP of Computational Engineering, where he will work alongside Johannes Brandstetter on AI for engineering, physics foundation models and large language models.
Neil reflects on the career decisions that took him from Manchester and Formula 1 to Oxford, NASA collaborations, AWS and NVIDIA. He shares what he learned from moving between academia and industry, how open datasets became central to his work, and why the chance to keep learning and build something new made Mistral an exciting next step.
For students, researchers and engineers considering a change, the episode also offers a personal perspective on developing a specialism, keeping an academic mindset in industry, and staying open to opportunities without needing to plan your entire career in advance.
Topics include:
Getting a first break in Formula 1
Switching between academia and industry
Learning HPC, cloud computing and product engineering
Machine learning, open datasets and scientific collaboration
NVIDIA's hardware, software and partnership ecosystem
Why Mistral, and working with Johannes Brandstetter
Career advice: expertise, continual learning and embracing change
Chapters: 00:00 Podcast intro 00:39 From NVIDIA to Mistral 01:46 My new role: physics AI and LLMs 03:18 Starting out in engineering and motorsport 06:26 A PhD and finding a specialism 08:38 Getting a first break in Formula 1 09:52 Returning to academia 11:57 Oxford, HPC and NASA 15:21 Consulting, Formula 1 and the connection to AWS 19:39 Leaving Oxford and joining AWS 21:06 Product engineering, ML and open datasets 23:29 What I learned at NVIDIA 26:39 Why Mistral felt like the next step 29:51 Career advice: stay open to change 31:28 Becoming known for a specialism 32:41 Podcast plans and closing thoughts
Paper mentioned: Fluid Intelligence: A Forward Look on AI Foundation Models in Computational Fluid Dynamics Neil Ashton, Johannes Brandstetter and Siddhartha Mishra https://arxiv.org/abs/2511.20455
These are personal reflections on my own career and experience.
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