Platform Scientist, Soft Materials

External

Lilasciences · Cambridge, UK

$108K–$150K/yrFull-timeOn-site1mo ago

3D PrintingData AnalysisMovePrototypingPython

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Benefits

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.Expected Base Salary Range$108,000 - $150,000 USDAbout LILALila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.We're All InLila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy .A Note to AgenciesLila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science's intDental insuranceVision insuranceFlexible scheduleEquity / stock optionsPerformance bonusParental leave

Additional Information

Your Impact at LILA Lila Sciences is seeking Platform Scientists, Soft Materials Focus to ideate, prototype, and transfer new experimental concepts for AI Science Factories targeting complex and soft material systems. In this role, you will work at the forefront of scientific ideation-partnering with a broad range of chemistry, materials, and AI teams to define new approaches to formulation, structure-property relationships, and performance evaluation. You will translate these concepts into scalable experimental workflows, custom apparatus, and software-enabled systems for autonomous research. What You'll Be Building Collaborate with diverse scientific teams to ideate new experimental strategies for soft and complex materials, including formulations, colloids, polymers, gels, and biological or hybrid systems Lead conceptual development of characterization and performance workflows leveraging techniques such as SAXS, SANS, rheology, and formulation performance assays Design, prototype, and validate custom apparatus, experimental methods, and software tools to realize these concepts Develop and refine workflows that connect structure, dynamics, and performance across multiple length and time scales Transfer successful prototypes into production-ready systems within Lila's AI Science Factory platform, enabling autonomous experimentation What You'll Need to Succeed MS or PhD in Materials Science, Chemistry, Chemical Engineering, Physics, or a related field, with a focus on soft or complex materials Demonstrated experience collaborating across scientific disciplines to generate and refine experimental concepts Hands-on experience with one or more of the following: SAXS, SANS, rheology, formulation performance or functional assays Experience designing and implementing custom experimental workflows and/or scientific software Strong programming skills (e.g., Python, C++, or similar) applied to data analysis, automation, or experiment control Excellent communication skills and comfort operating in a fast-paced, exploratory R&D environment Bonus Points For Experience with lab automation, high-throughput experimentation, or instrument control software Background in formulation science (e.g., consumer products, coatings, energy materials, bio-soft matter) Experience linking scattering, rheological, and performance data to predictive or ML-driven models Familiarity with prototyping tools such as 3D printing, machining, microfluidics, or custom sample environments Industry or national lab experience working on soft materials or complex fluids

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