{"id":701030,"url":"https://alion.io/job/periodic-research-scientist-materials-characterization","title":"Research Scientist, Materials Characterization","company":{"id":685855,"name":"Periodic Labs","domain":"periodic.com","url":"https://alion.io/company/periodic","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":85,"open_postings":31,"ghost_share":0.258,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":51,"computed_at":"2026-11-01T06:10:25Z"}},"role":"Science & Research","role_family":"Science & Research","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Menlo Park, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":250000,"max":350000,"currency":"USD","period":"year","gross":null,"usd_annual":350000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-07-09T22:42:04Z","employer_posted_date":"2026-07-09","last_verified_at":"2026-11-01T13:03:00Z","board_verified":true,"closed_at":null,"days_open":114,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":114},"description":"About Periodic Labs\nWe’re an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what’s scientifically possible.\nAbout the Role\nJoin a world-class team of scientists and engineers pushing the boundaries of materials research in a groundbreaking lab where AI and automation unlock discoveries at unprecedented speed and scale. As a Research Scientist within the Periodic Labs experimental effort, you bring AI predictions into reality through physics and measurement science. In this role, you will both develop new material characterization approaches and be part of the team developing autonomous discovery loops.\nThis is a senior, hands-on role. You will own the design and execution of high-fidelity property measurements, drive the development of high-throughput characterization schemes, and collaborate closely with AI, automation, and materials science teams to build feedback loops that accelerate discovery. You will set the standard for measurement quality and data integrity across the lab.\nWhat You’ll Do\nDevelop and perform high-fidelity thermodynamic, transport, and spectroscopic measurements of materials, including electronic, magnetic, and thermal properties\n\nDesign and implement rapid property measurement schemes to scale up the material characterization process and feed AI-guided discovery pipelines\n\nIn collaboration with the AI team, implement automated data analysis and reasoning pipelines for screened materials; contribute to feedback loop design between measurement and prediction\n\nIn collaboration with the engineering team, develop autonomous systems for property characterization leveraging robotics and programmable instrumentation\n\nEvaluate, procure, and commission new instrumentation; develop custom measurement setups where commercial solutions are insufficient\n\nDefine and enforce data standards, metadata schemas, and documentation practices to ensure measurement outputs are reproducible and reusable\n\nUphold and contribute to lab safety standards, particularly around cryogenic systems, high-field magnets, and hazardous materials\n\nYou Will Thrive in This Role If You Have\nPhD in Physics, Materials Science, or related field, with 5+ years of hands-on experience in physical property characterization\n\nDeep, demonstrated expertise in electronic and magnetic property measurements, including resistivity, Hall effect, magnetometry, and heat capacity\n\nStrong background in cryogenic measurements and low-noise techniques, including lock-in methods, shielding/grounding, and precision instrumentation\n\nStrong track record of highly impactful research demonstrated by publications in top-tier journals and/or inventions, and recognized leadership in the field\n\nProficiency with data analysis (e.g., Python/Jupyter, familiarity with instrument SDKs a plus) and disciplined data management practices\n\nExcellent scientific writing, cross-disciplinary collaboration, and strong ownership of experiment quality\n\nAbility to communicate measurement requirements and findings clearly to AI, engineering, and materials science collaborators\n\nEspecially Strong Candidates May Also Have\nExperience with automation of physical property measurement platforms (e.g., PPMS, MPMS, custom rigs)\n\nExperience with the computational prediction and experimental characterization design loop\n\nExperience with spectroscopic characterization techniques such as ARPES, neutron scattering, or optical spectroscopy\n\nExperience with lab buildout, instrument commissioning, and process safety\n\nExperience handling and managing data at scale, including LIMS or similar data infrastructure\n\nPrevious work at national laboratories or large-scale user facilities\n\nMechanics\nMinimum education: Bachelor’s degree or similar experience\nEmployment type: Full-time, 12-month term\nLocation: Menlo Park\nCompensation: $250,000-350,000 + equity\nVisa sponsorship: Yes, 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