Neil Ashton’s work has involved F1 cars and NASA rockets. He helps companies understand the immense speed of supercomputers and the power of machine learning. Whether he’s publishing a podcast or cycling, moving fast has been a golden thread woven through his life. But there are some things Ashton doesn’t rush.
He took five years to get his PhD in aerospace engineering. He loves a good tale, and you’ll often hear him say, “to cut a long story short…” And he encourages young engineers to take their time to build strong professional networks, rather than relying on blind hope.
Scientists are no strangers to paradoxes, and Ashton (38) has turned this fast-slow one into an exciting career.
Looking to the stars
Ashton describes himself as a translator between the worlds of science and engineering – a “meeting in the middle”, to use his words.
He’s a global tech lead for computer aided engineering at Amazon Web Services (AWS) and an active member of IMechE, helping young engineers “get the bug and stay” in the industry.
Born near Manchester, Ashton grew up in North Wales. His father was a university lecturer, but there were no engineers in his family. Ashton was drawn to science, his gaze fixed on stars and the pages of books like Stephen Hawking’s A Brief History of Time. He thought about space travel, watched Star Trek and harboured dreams of working at NASA (although at the time he was convinced it couldn’t happen because he wasn’t an American citizen). On weekends, he played bass guitar in a band that landed occasional gigs and weddings.
The engineering engine starts
After school, Ashton was searching for his next frontier when he discovered the “gulf” between reading popular science books and studying fundamental physics. He wanted excitement, a way to see how formulas applied in the real world. He found aerospace engineering at the University of Manchester. But after a while, even that began to feel distant from the adventures he’d imagined.
“What saved me,” Ashton remembers, “is when we had to do a placement to get some real-world experience.”
He emailed all the F1 teams he could find. None got back to him. So, he tried the next best thing: F2 (known as GP2 at the time). At first, the results were much the same. Until one team wrote back and offered him a project, which involved testing their car’s rear wing.
“I got to do wind tunnel testing,” Ashton explains. “The team also took me on the road with them. I shadowed their engineers and went to Grands Prix. This invigorated me.”
Study long and prosper
With his degree in hand, Ashton cast out some lines, hoping to find a job in racing. But with a limited network, there were no bites. He’d never thought about doing a PhD, but when the opportunity presented itself, he settled on staying a student for a few more years.
“I didn’t feel ready to go into the industry. I didn’t have any special knowledge. But after the PhD, I felt more aware of what I wanted to do. I felt I had a role to play.”
During those years Ashton wrote for the university newspaper, played in bands and explored aerodynamics, high-performance computing and machine learning. He found the field he would later specialise in.
His PhD proved to be the key that finally unlocked a job with an F1 team. Ashton moved to Oxfordshire, where he’s still based, to join what is today the Alpine team. But after some time he was back in academia, keen to expand his knowledge in areas outside of F1. He studied, worked at the University of Oxford and even moved to California for a while, joining NASA as a visiting scientist. Later on, the student who couldn’t get an F1 team to answer an email became the expert Formula One Management (the global umbrella organisation) hired to help overhaul its 2021 technical regulations.
A wave of opportunity
Using his knowledge of aerodynamics and computer simulations, Ashton found himself in rooms with legendary F1 engineers like Pat Symonds, Ross Brawn and Nikolas Tombazis. He also knew enough about the cloud and high-performance computers to become the bridge between F1 and its tech partner AWS. Another key turned, and Ashton took a job at AWS.
“Companies are really keen to find people for the next decade of innovation,” he says. “AI and machine learning are transforming our industry. This is a huge area that all engineers need to be aware of.”
Whether it’s designing aircraft components or bringing new medicines to market, Ashton believes AI has massive potential to help engineers and scientists. He says graduates can now join a company and bring with them fresh knowledge – things their managers don’t have experience in – and accelerate their careers.
“There’s also a new wave of opportunities for jobs,” he adds. “Whatever your hobby is, there’s engineering involved. Engineering is unique like that. You can get your dream job.”
‘Productivity enhancer’
Ashton doesn’t share some of the fears that have been expressed about AI. His take is that the technology will remain a tool.
“It will be a productivity enhancer. It can help you get to 80%, but you’ll still need to do the final 20%. It will get you a good answer, but struggles to get to the perfect answer.”
Ashton is using AI to boost his own productivity and on tasks like learning a new coding language. But behind his desk you’ll find a couple of guitars hanging on the wall – a reminder to go back to a dormant hobby, which took him a long time to master.
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Content published by Professional Engineering does not necessarily represent the views of the Institution of Mechanical Engineers.