Research Scientist, Polymer Physicist

The Materials and Systems Innovation (MSI) group, in Meta's Reality Labs Research, creates and accelerates breakthrough materials and device technologies that unblock the path to low-cost, all-day wearable AR devices and advanced sensing and actuating systems for robotics. We identify key technology gaps requiring step-change innovation, build AI-driven autonomous discovery pipelines to compress development timelines, leverage external partners to accelerate research, and deliver high-quality technology solutions through cross-functional, high-performing teams.

• PhD in Polymer Science, Polymer Physics, Chemical Engineering, Materials Science, Chemistry, Physics, or a closely related field 6+ years of combined postdoctoral and/or industry research experience in computational or theoretical polymer science
• Demonstrated depth in polymer theory and computational modeling – statistical mechanics of polymers, viscoelasticity and rheology, transport phenomena, and multiscale simulation methods
• Demonstrated ability to work directly with experimentalists: understanding experimental methods, interpreting characterization data, and using models to guide bench work
• Evidence of technical leadership – leading projects or sub-teams, mentoring scientists, and driving multi-person research agendas to results, navigating complex stakeholder management
• Track record of peer-reviewed publications and effective written and verbal communication with both specialist and cross-functional audiences
• Hands‑on experience with ionic polymer systems such as ionomers, polyelectrolytes, ion gels, polymer networks, and IPMC actuators
• Background in polymer synthesis and processing methods to guide manufacturability, formulation, and synthetic feasibility
• Hands‑on experience with molecular simulation and/or coarse-grained modeling packages (e.g., LAMMPS, OpenMM, ASE, HOOMD) and high throughput simulation
• Experience with polymer experimental characterization and failure analysis
• Knowledge of LLM‑driven automation, high‑throughput testing, self‑driving laboratory setups
• Experience with academic collaborators, industry consortia, and vendor engagement to advance technical goals
• Demonstrated history of establishing novel research initiatives and technical programs from initiation
• Familiarity with polymer informatics, public soft matter repositories, and machine learning potentials
• Working literacy in AI/ML for materials design: practical experience applying ML property prediction, surrogate modeling, or generative design to molecular or polymeric systems
• Experience in sensor and actuator technology, including electromechanical transduction, dielectric elastomeric materials, piezoelectric polymers, and soft robotic systems