Principal Scientist / Associate Director, Soft Materials Experimentation

Lilasciences; Cambridge; On-site; GBP 118,000 - 162,000; Full time

Benefits offered by this job

Equity

Job summary

Lila Sciences seeks a Scientific Leader to build and run a soft materials team spanning formulation, polymers, gels, and coatings. You will mentor four scientists and shape the portfolio over multiple years, ensuring robust measurement strategies and high-throughput workflows.

You will balance bench work with strategic leadership, drive data-rich campaigns, and collaborate with AI colleagues to close the loop from candidate to validated formulation across sites.

Qualifications

• PhD or equivalent depth with 8+ years of post-degree R&D experience
• Leadership experience in scientific teams or as technical lead
• Deep soft-matter fundamentals: phase behavior, self-assembly, rheology, interfacial phenomena
• Hands-on record formulating and characterizing multicomponent systems
• Experience delivering on milestones with industrial partners or sponsored programs
• Data-centric experimental practice: DoE, high-throughput methods, structured capture, ML collaboration
• Ability to navigate between strategy and bench-level troubleshooting, multiple sites

Responsibilities

• Lead and grow a group of scientists across formulation, polymer processing, and characterization; hire and set direction
• Own the experimental strategy for soft materials; define campaigns and ensure scientific validity
• Deliver on partner-funded programs with program managers; manage timelines and data quality
• Build high-throughput workflows for rheology, scattering, thermal and mechanical analysis, microfluidics
• Define measurement strategies enabling machine learning and inverse design; collaborate with modeling teams
• Collaborate with automation and engineering to move workflows into production with reliable control
• Provide technical depth on new opportunities; scope and customer-facing engagement
• Manage capital equipment and vendor relationships; ensure safe handling and regulatory compliance
• Coordinate shared characterization across cross-domain campaigns with other groups

Skills

Team leadership

Soft matter fundamentals

DoE / high-throughput methods

Machine learning collaboration

Bench experience

Cross-site collaboration

Python

Education

PhD in Materials Science / Polymer Science / Chemical Engineering / Chemistry

Tools

Python

Job description

Your Impact at LILA

Lila is hiring a Scientific Leader to build and run our experimental soft materials team, covering formulations, polymers, colloids, gels, emulsions, inks, adhesives, and coatings. You will take on a group of four scientists and grow it as the portfolio expands across formulation, rheological and scattering characterization, and polymer processing. The team turns soft-matter problems into closed-loop autonomous workflows: defining what gets measured, how it gets measured at throughput, and how the resulting data supports active learning and inverse design. The work asks you to stay close to the bench while mentoring a growing team and setting its direction over a multi-year growth horizon.

What You'll Be Building

• Lead and grow a group of scientists spanning formulation, polymer processing, and physical characterization; set scientific direction, develop the team, and hire against an expanding portfolio
• Own the experimental strategy for soft materials — the measurement stack, the campaign designs, and the scientific validity of what the group publishes internally and to partners
• Hold your team's delivery on partner-funded programs alongside the technical program managers who own the programs themselves, setting the standard on timelines, throughput, and data quality
• Build and validate high-throughput workflows spanning melt and solution rheology, scattering, thermal and mechanical analysis, microfluidics, and application-specific performance testing
• Define the measurement strategies that make machine learning and inverse design tractable, and partner with modeling and AI colleagues to close the loop from proposed candidate to validated formulation
• Work with automation and engineering colleagues to move prototype workflows into production with reliable instrument control, structured data capture, and end-to-end robotics
• Provide technical depth on new opportunities: feasibility assessment, scoping, and customer-facing scientific engagement
• Justify and manage capital equipment and vendor relationships for the group; set the expectation on safe handling for its chemical footprint and hold the group to it
• Coordinate shared characterization capability and cross-domain campaigns with adjacent materials and chemistry groups

What You'll Need to Succeed

• PhD in Materials Science, Polymer Science, Chemical Engineering, or Chemistry with 8+ years of post-degree R&D experience, or equivalent depth built through industrial practice
• Experience leading scientific teams, whether as a formal manager or as a technical lead with direct responsibility for others' work
• Deep soft-matter fundamentals: phase behavior, self-assembly, rheology, interfacial phenomena, colloid and dispersion stability, transport, cure and crosslinking
• Hands-on record formulating and characterizing multicomponent systems and translating structure–property relationships into performance
• Demonstrated delivery against external milestones with industrial partners or sponsored programs
• Data-centric experimental practice: DoE, high-throughput methods, structured capture, and working with ML colleagues as a peer rather than a customer
• Comfort moving between strategy and bench-level troubleshooting, and leading a team split across multiple sites

Bonus Points For

• Depth in one or more application areas such as adhesives and coatings, printed electronics, energy materials, or consumer and personal care
• Experience taking formulations from lab through scale-up and manufacturability review
• Robotic or automated formulation, automated characterization, or self-driving lab environments
• Python proficiency for analysis, instrument control, or workflow orchestration
• Familiarity with EHS and regulatory constraints on formulated products

Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits.

Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

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

$156,000 — $214,000 USD

About LILA

Lila 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.

LILA combines advanced AI models with proprietary AI Science Factory instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance.

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