Job Description
Key Responsibilities
- Design, develop, and execute experiments for the creation, modification, and characterization of innovative polymer materials and formulations, including adhesives, composites, elastomers, and coatings.
- Independently scope, plan, and manage complex R&D programs, establishing project objectives, timelines, and resource needs while partnering with engineering, manufacturing, and product development teams.
- Build fundamental understanding of materials–process–structure–property relationships to solve complex technical challenges and support process optimization within manufacturing.
- Analyze experimental data using advanced analytical tools (NMR, FTIR, GPC, DSC, TGA, etc.) and prepare high-quality technical reports, presentations, and recommendations for key stakeholders.
- Identify emerging technologies, develop novel concepts, and contribute to intellectual property strategy through invention disclosures and patent support. Stay current with scientific literature and industry trends.
- Provide technical coaching and direction to junior scientists and technicians, fostering a collaborative, high-performance, and safety-focused lab environment.
- Ensure all R&D activities align with regulatory, quality, and safety requirements (e.g., ISO, GxP), maintaining strong documentation and adherence to best practices.
Qualifications
Education:
- Advanced degree (Ph.D. preferred; M.Sc. considered) in Polymer Science, Chemistry, Materials Science, or Chemical Engineering.
Experience:
- Minimum of 10 years of industry experience in polymer synthesis, formulation, characterization, or application development.
Technical Skills
- Strong hands-on experience with polymer synthesis methodologies and advanced characterization techniques.
- Proficiency with analytical instrumentation such as NMR, FTIR, GPC, mass spectrometry, rheology, DSC, and TGA.
- Working knowledge of polymer processing techniques (extrusion, injection molding, mixing, etc.) is highly desirable.
- Experience with statistical experimental design (DOE), data modeling, and analysis tools.
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