Lila Sciences
Research Scientist, Computational Condensed Matter Physics
Cambridge, MA USA · Full-time
Sponsorship not specified$176k-$304kDetected 50 days ago
PythonMachine LearningAgentic AIRecruitingResearch
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odds of building a lasting career here
61Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
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Files H-1B transfers
10 transfer filings in the last year, covering 10 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
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About the role
- Your Impact at LILA Your role will involve applying computational condensed matter physics and electronic structure expertise to accelerate materials discovery, optimization, and understanding.
- You will use first-principles modeling, atomistic simulations, scientific machine learning, and agentic AI systems to investigate complex materials with direct relevance to superconductors, quantum materials, or electronic devices.
- You will work at the intersection of physics-based simulation, AI/ML, and autonomous scientific workflows.
Responsibilities
- 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 Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges.
- Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
Nice to have
- Apply computational condensed matter physics to materials discovery and optimization.
- Use computational physics methods (such as electronic structure and phonon calculations) to study quantum materials, superconductors and electronic devices.
- Analyze simulation and experimental data to generate actionable materials hypotheses.
- Communicate physical insights, model limitations, and recommendations to collaborators.
- PhD or equivalent experience in Physics, Materials Science, Chemistry, Applied Mathematics, or a related field.
- Strong foundation in computational condensed matter physics, electronic structure, or atomistic simulation.
- Deep understanding of electronic-structure theory (quantum chemistry, DFT, beyond-DFT methods, etc.) and their application to electronic, magnetic, or quantum materials.
- Experience applying first-principles or atomistic methods to materials discovery, optimization, or understanding.
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.
- 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
- Expected Base Salary Range
- $176,000 - $304,000 USD
- USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Benefits
- 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
- International Benefits.
- Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region.
Visa & Work Authorization
- al employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status
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This listing is sourced directly from Lila Sciences's careers page and normalized into a canonical job model.