Position:
Founding Scientist / Co-Founder
Company:
Clera
Location:
Germany (on-site)
Employment type:
Full Time
Short Summary:
This is a rare opportunity to join as a Founding Scientist / Co-Founder at an early-stage startup at the intersection of AI and wet-lab biology, operating within the aerospace and defense sector. You will combine hands-on biological expertise with computational thinking to shape the company's scientific strategy and core technology.
Responsibilities:
- Define and lead the scientific vision and research roadmap for early-stage AI + wet-lab products.
- Design and execute key experiments in molecular biology, biochemistry, or genomics to validate models and assays.
- Collaborate closely with engineers and ML researchers to translate experimental needs into computational requirements.
- Implement and oversee lab automation and data pipelines to scale experiments and improve reproducibility.
- Prototype computational tools and analyses; contribute code or notebooks integrating wet-lab data with models.
- Mentor and recruit early scientific hires; establish laboratory best practices and safety standards.
- Help navigate sector-specific constraints unique to aerospace and defense applications.
Requirement:
- PhD in Biotechnology, Genomics, Biology, or a closely related field.
- Senior-level research experience in molecular biology, biochemistry, genomics, biotech, or equivalent industry background.
- Demonstrated experience applying AI/ML to biological data (computational biology, bioinformatics, or similar).
- Experience in or familiarity with aerospace or defense domains, including an understanding of sector-specific constraints.
- Comfortable with computational thinking and coding; experience with ML is a strong plus.
- Must be eligible to work in Germany without visa sponsorship.
Benefits:
- Opportunity to work at the frontier of AI-accelerated biology.
- Join a team that values intellectual curiosity and a bias toward action.
- Contribute to building systems that integrate machine learning models with experimental wet-lab workflows.