We need a new superstar.

You are an expert in your field, fed up with the waste of internal sync meetings and frustrated by opportunities being lost. You see the potential of AI, high-speed simulation and real-time optimization in plasma and high-temperature processes, but you are probably being held back by legacy systems, corporate politics, company strategy or general risk aversion.

What we want to do has not been done before.

What we are building

We started GREEN14 five years ago with a mission: to help Europe develop emission-free production of critical raw materials using hydrogen plasma.

The fact that we started on the production side matters. We have access to a fully operational plasma reactor where we run experiments every day. As a scientist, you know what that means: models get better when they can continuously learn from real-world data.

We have invested extensively in our multiphysics models, internal solvers and surrogate models. Our approach has been reviewed by external experts, and while we have yet to deploy it on external industrial processes, we believe it has the potential to bridge a gap that still exists between process engineers and simulation engineers.

Many global industrial companies still operate processes that are effectively black boxes. They know the output they want and they know how they operate the process today, but they lack fast, reliable models that can tell them how to change parameters, materials or geometry to optimize for a new target output.

That is the problem we want to solve.

Your role

You will lead or co-lead a small but growing team of experienced engineers working across simulation, physics and AI.

Today, that capability spans multiphysics modelling, internal solvers, AI and high-performance scientific computing. You will own the computational architecture that brings these pieces together — from high-fidelity physics models and accelerated solvers to surrogate models and, ultimately, real-time process optimization.

You will work closely with our process team in a genuine two-way exchange: you help them understand and improve the physical process, while experiments and reactor data help you improve the models.

This feedback loop is one of the things that separates us from most simulation companies. We don't just simulate a process. We can run it, measure it, change it and run it again.

The ambition is to move from high-fidelity multiphysics simulation toward fast, trustworthy surrogate models that can ultimately help engineers answer a much more valuable question:

What should I change to get the product I want?

You will also help determine what comes next: which models we build, which capabilities we add, where AI creates real value and how we turn our technology into something industrial customers actually use.

Who you are

You have a PhD in a relevant field and deep experience in areas such as multiphysics modelling, CFD, plasma physics, high-temperature chemistry, numerical methods or scientific computing.

You understand the strengths and limitations of physics-based solvers, surrogate models and machine learning. AI isn't something you recently learned because the market moved in that direction — it is already part of how you think about solving complex scientific problems.

You are curious about new industrial use cases and enjoy working directly with both modellers and process engineers. You care about whether what we build actually solves problems customers face every day.

You are also comfortable explaining complex ideas. Engaging with customers, industrial partners and the research community will be a natural part of the role.

And if there are things we are missing, you tell us. We are humble enough to change our approach when someone has a better one.

How we work

You'll join a team of serious engineers and scientists who care deeply about getting things right.

We're international, curious and direct. We challenge each other's thinking, share what we know and change our minds when the data tells us to.

There is very little hierarchy and no room for corporate politics. Good ideas matter more than titles, and we expect people to speak up when they think we're wrong.

We're ambitious, but low on ego. We help each other get better because the problem we're trying to solve is genuinely hard — and none of us can solve it alone.

We work hard, but flexibly, and we value having a life outside work.

Where this can go

The team is small today, but our ambitions are not.

Market traction and revenue will determine how quickly we can scale, so you should be excited by the prospect of building both the technology and the team around it.

This is not a role where everything has already been defined. You will have significant influence over our technical architecture, research priorities and how we turn simulation and AI into a product that industrial customers actually use.

If we succeed, what we build will not be limited to one reactor, one material or even one process. The ambition is to build a computational approach that can help engineers understand, optimize and scale complex high-temperature processes across industries.

The practical stuff

Compensation consists of salary and pension together with qualified employee stock options.

We are based at Sweden's leading technical university, five minutes by Voi from central Stockholm. There is a reason for that location: we want the simulation team close to the plasma reactor, the experiments and the people running them.

Don't be a stranger. Apply, or connect with Quentin or CEO Jan Dinkelspiel on LinkedIn.

The position will remain open until we find the right person — whether that is tomorrow or a few months from now.

We look forward to hearing from you.