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Cruising through racing’s McLaren Technology Group

Dr Caleb Sawade

Bachelor of Engineering (Electrical & Mechatronic) with Honours
Modelling & Decision Sciences Manager at McLaren Applied Technologies
Racing car simulator

While studying his degree in engineering at the University of South Australia, Dr Caleb Sawade was offered the opportunity to undertake an internship with the McLaren Technology Group in America – a household name in motorsport and Formula One since its creation in 1966. What happened next was a series of events that he could never have foreseen, landing him with a PhD to top it off.

Dr Sawade discusses his transition from technical intern to modelling and decision sciences manager, breaks down the inner workings of McLaren, and delivers some insightful advice for new graduates.

Please briefly describe your journey from studying a Bachelor of Engineering (Electrical & Mechatronic) with Honours, to where you are now

During my undergraduate studies at UniSA, I travelled to the USA to work for McLaren in a technical internship. It was a great experience and exposed me to the high-paced engineering of motorsport. Towards the end of the placement, they asked to sponsor my final year honours research project: a rehabilitation simulator for the GB (Great British) Rowing team.

After completing my degree, I began working as a Mechatronic and Systems Engineer at SMR Automotive in South Australia. The position allowed me to experience multiple areas of the business and understand in more depth the manufacturing in the automotive market.

A year later, McLaren offered to sponsor a PhD, in the UK, on one of many proposed ideas. The list was fascinating, but I declined as I wasn’t interested in doing a PhD. After some persuasion from the technical director, Dr Caroline Hargrove, I decided to go for it, packed my bags and moved to the UK – not without my fiancé, of course.

It was the best career decision I have ever made. The PhD at Southampton University was an incredible experience. It was focused on how to use virtual environments and robotics, to accelerate the rate of elite athlete learning. I worked with TeamGB and UK Sport to develop simulators for extreme sport and Olympic programmes, subsequently leading to a gold medal at the Olympics. It was a slightly strange PhD, as although it was an Engineering Sciences Doctorate, there was a large amount of cognitive and neuroscience research, which was a steep learning curve. At the end of the PhD, I consulted for UK Sport and the English Institute of Sport on sports such as Rowing, Sailing, and Cycling, before joining McLaren Applied Technologies full-time.

Now, as the Modelling and Decision Sciences Manager, I manage the data science, simulation engineering, and business analytics disciplines within the business. It’s amazing to work with such a talented group of people on some really exciting projects.

Please describe your position at McLaren Applied Technologies in the UK

McLaren Applied Technologies (MAT) is one of the McLaren Group companies, consisting of McLaren Racing (the Formula One team), McLaren Automotive (a high-end supercar and hypercar manufacturer), and McLaren Marketing (an exclusive brands and marketing company). MAT is mix between a consultancy and product company. We work on internal products, and with clients, across multiple industries to bring high performance engineering and software to the wider world. The business is focused on five key industry areas: motorsport, automotive, public transport, health and wellness, and strategic partnerships. Each are connected by common technologies we develop and scale across industries. We work closely with McLaren Racing and McLaren Automotive to help them develop the latest technical advancements in their respective fields.

Unfortunately I can’t discuss most of what we do as we confidentially work for fortune 500 companies and interact on technical development years before they enter the marketplace. These technologies cover everything from autonomous vehicles, medical devices, transportation systems, and consumer goods. But there are a few examples I can discuss.

Racing car simulator

Born out of Formula One, we develop simulators for the automotive industry. Human-in-the-loop driving simulators are not a new idea for car manufacturers, however most of them are used for driver training, ergonomic assessment, or safety testing. Our latest simulator changes this, as it reproduces the sensations of driving very well, allowing engineers to develop the car not the driver. Performing vehicle dynamic assessment in a virtual world drastically reduced development costs. It means we have had to model the car in great detail and understand how humans perceive driving. Our focus is to ensure the driver makes the same decisions they would in the real car. By making the same decisions, we can understand how to best manipulate the car to maximise driver enjoyment. McLaren Automotive is one of our clients who we help develop cars like the McLaren P1 and 720s.

Bike design

We have worked with US bike manufacturer Specialized for years. Initially we took our Formula One know-how of composite materials and applied them to bike design and manufacture. This reduced the weight and increased the stiffness. But we didn’t want to stop there, we wanted to know how and why an increase in stiffness alters the riding experience. So we built a dynamic computational model of a bike and rider. Every detail possible was added – from tyres rolling over stones, to the forces the rider exerts on the handlebars. The model allows Specialized to optimise key performance metrics of all their bikes before they even build one.

My focus at the moment is building and managing the Modelling and Decision Sciences team, soon to be around 40 engineers. We work on all areas of the business and are expanding fast. Our approach is novel because we mix Simulation Engineering, which is concerned with the fundamental physics and detail of how things work, with the newer field of Data Science, which is taking data and building machine learnt models to quickly understand problems. Most companies normally have one or the other, but our approach with both means we develop novel algorithms, which outperform those previously developed. We are the algorithm factory of the company, and together with our software development and hardware teams we create novel products you probably interact with daily.

What is your best piece of advice for recent graduates?

Learn as much software programming, data handling and mathematics as possible. All industries need it, and it will compliment all degrees.

Don’t be afraid to go back to university, undergraduate or postgraduate degrees, as it will enable you to learn and be qualified in what you love.

Spend equal amounts of time building a good team, as worrying about your own career – people will follow you if you have their backs, and together you will succeed faster.

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