Staff Materials Research Scientist, PFAS Alternative Discovery

What you'll do

• Lead partner engagements to define target specifications, constraints, and qualification criteria; translate validation results into actionable improvements.
• Run the generative chemistry workflow, assess and rank compounds, and validate candidates against semiconductor process, performance, and EHS requirements.
• Coordinate with internal data, computational chemistry, machine-learning, and generative-modeling teams to align targets and screening objectives.

What they ask for

• PhD in Chemistry, Chemical Engineering, Materials Science, or a related field, with deep specialization in semiconductor process materials and/or fluorochemistry.
• Working knowledge of semiconductor unit processes and process-material qualification requirements.
• Demonstrated ability to lead external industrial partner engagements and translate experimental results into computational or modeling requirements.
• Proficiency in Python and familiarity with generative molecular design, high-throughput virtual screening, or ML property prediction.

Nice to have

• 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 with fabs, OEMs, or chemical suppliers; publications or patents in relevant fields are also valued.

Pay

$163.2K – $306K USD base salary

Tools

Python, generative ML, DFT, molecular dynamics, Large Quantitative Models

AI focus

Operates and evaluates generative chemistry discovery workflows and collaborates on machine-learning and physics-based simulation approaches for PFAS alternative discovery.