Domain Scientist (PhD)

About Mafer

At Mafer we are building an AI data platform for R&D teams in formulation industries: flavors & fragrances, food & beverage, cosmetics, personal care, home care and specialty chemicals. We structure the molecular and formulation data that today lives across instruments, spreadsheets and lab notebooks, and turn it into systems that accelerate analysis, formulation and regulatory work.

We are a small, highly technical team of engineers and scientists, working from our office in Barcelona and backed by tier-1 investors. Everyone here works close to customers: you are either building or selling.

The role

Our models are only as good as the chemistry behind them. We are hiring scientists who know one domain deeply, food, flavors and fragrances, or specialty chemicals, and want to put that knowledge into software that R&D teams use every day.

This is not a pure research role. It is a hybrid of three things: forward deployed (you sit with the client's formulators and quality teams), researcher (you decide what their data means and which models are worth building) and engineer (you ship, in Python, alongside our engineering team). We will hire one person per domain. The first priority is food.

What you'll do

• Own the science of your domain inside Mafer: which variables matter, which measurements can be trusted, which relationships a model can learn and which it cannot.
• Deploy with clients: run technical deep-dives with R&D, quality and regulatory teams, read their formulation history and lab data critically, and turn it into well-posed problems.
• Food: understand a product at the chemical and physical level, not only as a recipe. Ingredient functionality, proteins, fats, carbohydrates and emulsifiers, process and reaction chemistry, stability and shelf life, water activity, sensory and nutrition trade-offs such as sodium or sugar reduction, clean-label substitutions. Across categories: bakery, dairy, beverages, savoury, plant-based.
• Flavors, fragrances and chemicals: the same depth with odorants and volatiles, olfactive and taste profiles, stability, and the regulatory limits that shape a formula (IFRA, EU allergen rules, REACH).
• Build with the engineers: feature design, evaluation sets, validation against real trials, and the domain modules that encode what you know.
• Write it down: internal notes, and technical notes on our website when the work deserves it.
• What you will not do: publish papers as the main output (the output is a model or a module a client uses), run a wet lab (we work with the client's data and, when needed, their lab), or consult (everything learned deployed becomes product).

What we look for

• A PhD, or equivalent industrial depth, in food science, food chemistry, biochemistry, flavor or fragrance chemistry, chemical engineering, materials or a close field.
• Industrial experience: you have worked in or with a food, flavors & fragrances, cosmetics or chemical company (R&D, quality, analytical or regulatory), or in an industrial analytical laboratory, and you know how formulation and quality actually run there.
• Quantitative and hands-on with data: comfortable in Python (pandas, scikit-learn or similar), able to read a chromatogram, a design of experiments or a sensory panel and judge what it supports.
• Rigour and judgement: you can say "this data does not show that", and you can also say "this is good enough to ship".
• Comfortable in front of clients, in Spanish and English, and willing to travel to plants.

Nice to have

• Depth in one or more food categories (dairy, bakery, beverages, savoury, plant-based) at the chemical level: ingredient functionality, process, shelf life.
• Predictive models, chemometrics or QSAR-type approaches in your field.
• Instrumental data: GC-MS, LC-MS, NIR, rheology, texture analysis.

What we offer: an early equity package, a €5,000 relocation bonus and help finding housing near the office, 10% of your time on long-term research, and a front-row seat: your domain becomes a product line.

Hiring process

1. Apply below — we read every application and reply if there's a potential fit.
2. A 30-minute conversation with Fer (CEO) to get to know each other and align expectations.
3. A technical interview with Marc (CTO), around one hour.
4. Two days working on-site with us at the office in Barcelona, on a real Mafer problem: you see how we work and we see how you work.
5. We move fast: we aim to decide within three days of the last conversation.