Staff Materials Research Scientist, PFAS Alternative Discovery

SandboxAQ·United States·24 июля

Staff Materials Research Scientist, PFAS Alternative Discovery

🏢 ОфисSeniorПолная занятость

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Наша компания

SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact.

О роли

Introduction to the team: The PFAS team sits within SandboxAQ's Chemical Simulation (ChemSim) group. Our mission is to develop PFAS-lean or PFAS-free substitutes and formulations for semiconductor process and fab materials that meet both performance specifications and environmental and safety requirements in complex semiconductor manufacturing environments. We combine generative ML, physics-based simulation (e.g. DFT and molecular dynamics), Large Quantitative Models for property prediction, and multi-scale modeling with a partner-driven experimental validation loop — working alongside industrial co-development partners to move candidate molecules from prediction to qualified use

Чем предстоит заниматься

See how SandboxAQ is helping build America's semiconductor supply chain from the materials up

Own the partner validation loop. Serve as the primary scientific point of contact between the PFAS team and external co-development partners (e.g. chemical and process-materials suppliers, semiconductor equipment makers, and control/sensor companies), translating partner problems into well-posed target specifications, constraints, and qualification criteria

Run the discovery workflow and rank candidates. Operate SandboxAQ's generative chemistry discovery workflow for assigned PFAS-substitution use cases; assess the predicted compounds for chemical plausibility and use-case fit, and rank them to produce decision-ready shortlists that partners can take into experimental validation

Close the experimental feedback loop. Translate partner validation results and experimental data into specific, actionable technical improvement points for the rest of the team, and follow their incorporation through successive design cycles

Align targets across internal teams. Partner closely with internal dataset, computational chemistry, machine-learning, and generative-modeling teams to keep property targets, screening oracles, and reward objectives aligned with partner-defined qualification criteria

Наши требования

PhD in Chemistry, Chemical Engineering, Materials Science, or a related field, with deep specialization in semiconductor process materials and/or fluorochemistry

6+ years of post-PhD experience (or equivalent) in industrial or applied R&D developing, formulating, or qualifying semiconductor process chemicals — including direct, hands-on experience discovering or evaluating PFAS-lean/PFAS-free alternatives for semiconductor manufacturing and adjacent materials (e.g., wet-etch/clean chemistries, lithography materials, heat-transfer fluids, or data-centre/immersion cooling fluids)

Working knowledge of semiconductor unit processes (e.g. lithography, etch, CMP, cleaning, thermal management) and the performance and EHS specifications that govern process-material qualification

Demonstrated ability to lead application-driven engagements with external industrial partners and to translate fluently between experimental results and computational/modeling requirements

Proficiency in Python — sufficient to run and configure computational discovery workflows and interpret their outputs — and comfort collaborating with generative-ML and physics-based simulation teams

Familiarity with generative molecular design, high-throughput virtual screening, or ML property prediction for molecules and materials

Direct, hands-on experience with PFAS phase-out or fluorine-free reformulation in a fab or specialty-chemicals setting

Experience defining qualification protocols or reliability criteria jointly with fabs, OEMs, or chemical suppliers

Track record of publications or patents in semiconductor materials, fluorochemistry, or PFAS alternatives

Experience operating within a CHIPS Act or other federally funded R&D program

WHY JOIN US?

We offer competitive compensation, a comprehensive benefits package, and opportunities for professional growth

Мы предлагаем

Competitive base salary commensurate with experience, plus equity and performance-based incentives

Comprehensive health, dental, and vision insurance

401(k) with company match

Generous parental leave

Work-Life Balance: Flexible hybrid work arrangements, generous PTO, and a culture that respects focus time and recovery

Career Development: Direct exposure to CHIPS Act-funded programs, senior scientific and executive leadership, mentorship, and dedicated learning budgets to support continued growth

SANDBOXAQ WELCOMES ALL

We are committed to fostering a culture of belonging and respect, where diverse perspectives are actively sought and valued. Our multidisciplinary environment provides ample opportunity for continuous growth - working alongside humble, empowered, and ambitious colleagues ready to tackle epic challenges

Read: Guidance for candidates on using AI Tools in interviews

Дополнительно

Introduction to the role: The PFAS team is looking for a Staff Materials Research Scientist to serve as the scientific bridge between our generative chemistry discovery workflow and the external partners who validate our candidate molecules. This role is central to our efforts to ensure that the compounds our AI-driven workflow proposes are directionally correct, appropriate for the target semiconductor use case, and grounded in real manufacturing constraints. This person will: (1) own the partner-facing validation loop — serving as the primary point of contact with our co-development partners on problem definition, target specifications, constraints, and qualification criteria; (2) run our generative chemistry workflow, assess the predicted compounds, and rank them by fitness for the use case to deliver decision-ready shortlists for partner validation; (3) translate experimental feedback from partners into concrete technical improvement points that the rest of the team members can act on; and (4) bring semiconductor domain judgment to bear on the whole pipeline, deciding whether workflow outputs are qualitatively and directionally accurate and validating lead molecules against process reality

SandboxAQ

United States

ГрейдSenior

ЗанятостьПолная занятость

РегионСША

ФорматОфис

ИсточникСкрыто

Опубликовано24 июля

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