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Renasens AB seeks a PhD-/masters-level scientist to own the cotton pre-treatment and dye removal workstream. You will design and run lab-scale experiments, analyze data, and refine protocols to inform scale-up decisions.
You'll work onsite in Borås with a small, fast-moving team, translating results into actionable process improvements and contributing to lab operations.
At Renasens we're building for people who are energized by winning, enjoy ownership, and thrive in a fast-moving environment. Our pace demands individuals who hold themselves to a high standard and care deeply about execution.
If you prefer extensive structure, highly predictable environments, or a slower pace of decision-making, we may not be the right fit.
In a small team, there's nowhere to hide—in both directions. Great work gets noticed, and so do opportunities to improve. The upside is that your impact is visible, your contributions matter, and strong performance is recognized quickly.
Before applying, take a moment to consider whether this environment aligns with how you do your best work.
You see a chemical process and instinctively want to understand it in detail; not just whether it works, but why. You will bring a methodical mindset and real attention to detail, taking full ownership of the cotton pre-treatment and dye removal workstream. You are comfortable designing experiments from first principles, running them rigorously, and turning data into decisions that move the process forward.
Onsite & hands on: Our pilot plant is in Borås, with our headquarters in Stockholm. This role is based where the work happens; close to the lab and the pilot, not behind a laptop.
Expect to spend most of your time on site running experiments and iterating with the team.
Small team, high ownership: We are around 10 people. You will own your workstream end-to-end and work directly with the R&D lead, process engineers and CEO. No layers, no committees.
Pace matters: We have pilot reception milestones in 2026 and customer commitments behind them. We move fast, decide with the data we have, and iterate.
Full-time