R&D Scientist - Strain Engineering & Microbial Fermentation (All Genders)

BIOWEG is seeking a Scientist to join our R&D team. In this role, you will improve the economics and robustness of our bacterial fermentation processes while leading proof-of-concept studies that expand our product portfolio. You will own experiments end to end, from experimental design and execution to data analysis, working hands-on with bacterial systems and translating your findings into practical process improvements.

If you are passionate about applying biotechnology to develop sustainable materials and enjoy working in a dynamic startup, we'd love to hear from you. Join us and help shape the next generation of bio-based solutions.

• MSc or PhD in Biotechnology, Microbiology, Biochemical Engineering, Fermentation Technology, Food Technology, or related
• MSc with at least 4 years or PhD with at least 1 year hands-on applied/industrial fermentation experience (lab-scale; pilot exposure is a plus)
• Proven ability to optimize and troubleshoot fermentation processes (not just run them)
• Strong data analysis and scientific communication to turn unexpected runs into decisions
• Analytical experience (HPLC): implementing and running methods, interpreting chromatograms, reporting results clearly
• Structured, proactive working style with ownership, prioritization, and delivery mindset
• Comfortable taking end-to-end ownership in a small-team lab and start-up environment
• Excellent written and verbal communication skills in English

Strong plus (preferred) 

• Experience with bacterial cellulose or closely related microbial production systems
• Experience with valorization of side streams / process sustainability improvements (turning “waste” into value)
• Familiarity with bioacids and/or microbial preservation systems for food or cosmetics
• Comfort working across disciplines (R&D, scale-up, operations)

How you’ll be successful in the first months (clear outcomes) 

• Execute a repeatable experimental pipeline while further improving it(templates, key KPIs, sampling plan, reporting format).
• Deliver at least one cost-reduction / productivity improvement supported by data.
• Produce scale-up ready recommendations(what to change, why, expected impact, and risks).