We’re building the protein breweries of the future. Our process is up to 5,000× more land-efficient than animal or plant protein. In the coming years, we’ll run our first commercial facilities producing thousands of tonnes of protein.

This internship is about understanding what happens inside them. A fermentation is a living system you can barely see into, and almost everything we decide about it rests on inferring the rest.

What you’d be modelling

Our fermentation is a bacterial culture feeding on a renewable liquid feedstock, in a stainless steel vessel, for days at a time. The things you actually want to know — how much biomass is in there, how much product, whether the culture is healthy or about to stall — are the things you cannot measure while it runs. What you get continuously is the periphery: off-gas, feed rate, dissolved oxygen, pH, temperature, vessel weight, heat. The variables that matter arrive hours later from a lab assay, if at all.

So you infer. Everything downstream of that — control, scale-up, deciding what to run next — depends on how well.

The role

Our dataset is dozens of fermentations, not millions of rows, and each one costs weeks of plant time to produce. The work that follows from that is mechanistic modelling, Bayesian inference, statistics that takes uncertainty seriously, and design of experiments that earns its keep because the experiments are expensive. You reach for the process before you reach for the algorithm.

The other half of the job is being understood. You’ll be explaining what your model found to the process engineers and fermentation scientists who have to act on it, in terms of the process rather than the method. They’re in the same building, they know things your data doesn’t, and they will tell you when you’re wrong.

What you’ll own

One central project, yours end to end. See three ideas below: which one you take depends on where you’re strongest and what the plant needs when you arrive, and we’ll work that out with you.

Build a soft sensor. Infer the unmeasurable from the measurable: biomass and product concentration, live, from off-gas, feed rate and the rest of the online signals. State estimation on a real process. The end state is the interesting part — a good estimate doesn’t stay in a notebook, it goes into BrewControl and closes the loop on a vessel in this building.

Model the organism. A kinetic model of our strain, fitted against our run history, that predicts what a fermentation will do before it runs. Mechanistic where the biology is understood, data-driven where it isn’t, and honest about which is which. The deliverable is a model the fermentation team trusts enough to plan against.

Design the next experiment. When a single run costs a fortnight, choosing the right one is worth more than any analysis of the last one. Design of experiments over the process parameters, with a model of the process as the surrogate, choosing sequentially as results come in. The deliverable is the run we do next.

The bar is the same whichever you take: someone bets a fermentation on it — a real run, planned differently because of what your model said.

Who you are

You model from first principles. The instinct we’re screening for is reaching for the process before the algorithm.

Statistics, properly. Uncertainty, priors, mixed effects, experimental design. You should be able to say what your model doesn’t know.

Python, scientifically. The numerical and statistical stack, not just the ML one.

You’ve met real data. Messy, small, expensive, gappy, with a sensor that was miscalibrated for three weeks in the middle.

You can talk to a process engineer. Explaining a result in terms of the process, to someone who knows the process better than you do, is half of this job.

Fast learner. Excited to dive into fermentation biology and bioprocess engineering.

Mission driven. Rewriting how the world makes protein genuinely excites you.

Bonus points for: bioprocess or chemical engineering, state estimation and control theory (Kalman filters and friends), Bayesian methods, time-series at scale, a biology, physics or systems biology background, enough software engineering to ship what you build, previous startup experience.

How we work

Small, highly technical, deeply ambitious. Every person here matters.

Our pilot plant is in our Amsterdam headquarters. Your data doesn’t arrive as a CSV from a data warehouse — it comes off vessels you can walk downstairs and look at, and the people who ran them are at the next desk. When a number looks strange, you can go and find out why. You’ll work alongside the fermentation scientists and process engineers who generate it.

We build from first principles. If “industry standard” slows us down, we rewrite it. If you’re looking for a standard 9-to-5 internship, this is not it — your learning curve is as steep as you can handle.

Expected outcomes

• A model in production, changing how real fermentations are run

• Real depth in scientific modelling — inference under genuine uncertainty, on data you can’t get more of

• A working understanding of bioprocess, from the biology to the vessel

• Work on a process nobody else is running

Rewards

• A flat, fast, and curious team working on one of the most exciting challenges in food

• An international, high-talent, low-ego culture where ideas matter more than titles

• Room to grow into whatever version of the role you make yours

• Daily plant-based lunch, snacks, fruits, drinks

• In house gym & regular team sport activities

• Fun off sites & team drinks 

What we’re building

We’re going beyond the limiting constraints of photosynthesis. We use natural fermentation to turn simple ingredients into complex proteins. It’s what we've been doing for millennia with wine, beer, bread and yoghurt.

Yet most fermentations rely on sugars - which are derived from crops grown on agricultural land. Our fermentation platform relies on an easily storable and shippable renewable energy based feedstock. This allows us to break free from the limiting constraints of photosynthesis.

We’re building the spiritual successor to the Haber-Bosch process. While Haber-Bosch led to cheap synthetic fertilizer which currently feeds half of humanity, we have found a way to produce amino acid complete proteins up to ±5000X more land efficient than animals. By rough approximation this could multiply the carrying capacity of the earth by an order of magnitude. The result of our ambition should be visible from space.

About us

We’re a small, highly technical and deeply curious team with deep food and fermentation expertise with backgrounds from the Vegetarian Butcher, Perfect Day to Nature’s Fynd and many more.

We’re flat and interdisciplinary by design. We value autonomy, speed, and ambition. You’ll have the freedom to build, and the responsibility to do it well.

We’re based within the city ring of Amsterdam – for a reason. We want to attract the best people from around the world and believe that Amsterdam is a great place to settle – and bike to work. On top of that, the Netherlands is one of the most productive agricultural regions in the world. The Dutch have a mindset to push the boundaries of food production and have the practical expertise to scale up our fermentation platform.

We believe hardware startups can thrive in Europe. If we can get approval here, we can do it anywhere (and we want Europe to accelerate).

We’ve raised +€10M from world-class investors including World Fund, Vorwerk Ventures, Revent, and Nucleus Capital, and European and national grants.