Senior​/Chief Scientist R&D

We are seeking a pioneer researcher and scientific leader who works best at the frontier of a field, defines their own questions, and is energized by the absence of a roadmap.

Your mandate will be to identify, investigate, and de-risk platform-level opportunities in porous media materials and mechanisms that could define entirely new product categories. You will report directly to senior R&D leadership and operate with genuine scientific autonomy. Title will depend on experience and track record in the industry.

• Scan the porous media landscape nonwovens, polymer membranes, metamaterials, and other fibrous structures for convergence zones and white-space opportunities invisible from within a single material class.
• Formulate original research hypotheses, design experiments to de-risk them, and execute at TRL 1-3 with full scientific independence.
• Build and maintain an active presence in the external scientific community: publish, present, collaborate with academic partners, and serve as the scientific antenna in your domain.
• Apply computational and AI-assisted tools, including high-throughput experimentation, design of experiments, and Bayesian optimization, to accelerate discovery cycles.
• Communicate findings clearly to senior R&D and executive leadership: what you found, what it means, and, just as importantly, what you killed and why.
• Identify opportunities to connect emerging platform concepts to existing technical and manufacturing capabilities where genuine synergy exists.
• Lead or support the commercialization of platform concepts.

• PhD in a STEM discipline - Chemical, Mechanical, Materials Science, or another porous-media-related discipline or BS/MS degree with equivalent work experience.
• A track record of originating research and successful commercialization.
• First-author publications in peer-reviewed journals and/or named inventorship, not just assignee.
• 10+ years of product development experience.
• Cross-domain literacy across the porous media landscape, with deep expertise in at least one material class.
• Computational and AI fluency: proficiency in design of experiments and Bayesian optimization required;
  Python or equivalent scripting for data analysis strongly preferred; familiarity with high-throughput experimentation platforms or closed-loop optimization systems is a real differentiator.
• An active, generative external scientific network, demonstrated through conference participation, invited presentations, peer-review activity, or academic collaborations.
• The intellectual disposition to propose ideas that contradict current product logic and defend them with data.
• Previous technology scouting experience.