{"id":3545172,"url":"https://alion.io/job/lila-sciences-co-op-ai-driven-equation-discovery","title":"Co-Op, AI-Driven Equation Discovery","company":{"id":65163,"name":"Lila Sciences","domain":"lila.ai","url":"https://alion.io/company/lila-ai","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"A","score":88,"open_postings":39,"ghost_share":0,"stale_share":0.282,"repost_share":0,"time_to_fill_p50_days":85,"computed_at":"2026-11-09T06:03:00Z"}},"role":"Energy","role_family":"Energy","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cambridge, United States","San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":110000,"max_usd":262000,"period":"year","method":"role_country_seniority_unknown","sample_n":488},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Digital Twin","optional":false},{"name":"JAX","optional":false},{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false}],"status":"live","first_seen_at":"2026-10-30T19:22:34Z","employer_posted_date":"2026-10-30","last_verified_at":"2026-11-09T14:52:48Z","board_verified":true,"closed_at":null,"days_open":10,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":10},"description":"Your Impact at LILA\nThe PS AI team sits at the intersection of Physical Sciences R&D and AI/ML. Lila runs high-throughput experiments across electrochemistry, formulations, and advanced materials, generating rich datasets that demand more than black-box models.\nAs a Co-Op focused on AI-driven equation discovery, you will develop and benchmark methods that extract interpretable governing equations directly from that data. Discovered equations reveal the underlying physics, make predictions explainable, and serve as mechanistic building blocks for digital twins and closed-loop optimization.\nYou will work alongside PS AI researchers and physical scientists, helping shape how Lila turns experimental data into scientific understanding at scale.\nWhat You'll Be Building\nBuild end-to-end equation discovery pipelines from preprocessing through candidate generation and validation\nBenchmark symbolic regression methods (SINDy, PDE-FIND, PySR, LLM-guided search) on Lila campaign data\nApply equation discovery to live electrochemistry, formulation, and materials datasets\nDesign evaluation harnesses measuring recovery rate, generalization, noise robustness, and physical consistency\nEmbed discovered equations into surrogate models, physics-informed models, and experimental digital twins\nTranslate open scientific questions into concrete problems with datasets, baselines, and success criteria\nDocument and present findings across PS AI and domain science teams\nWhat You'll Need to Succeed\nPursuing a Master's or PhD in ML, CS, applied math, physics, materials science, or chemical engineering\nStrong Python skills with hands-on experience in PyTorch, JAX, or similar\nExperience applying machine learning to messy, real-world scientific or experimental data\nSolid grounding in linear algebra, calculus, and probability\nComfort reading and implementing methods from ML research papers\nAbility to frame open-ended scientific questions as concrete ML tasks\nClear communication across research, engineering, and physical science teams\nBonus Points For\nWorking knowledge of symbolic or sparse regression methods (SINDy, PySR, PDE-FIND, or equivalent)\nExperience with LLM-guided or agentic symbolic regression (LLM-SR, SR-Scientist, or similar)\nBackground in physics-informed ML, uncertainty quantification, or operator learning (PINNs, neural ODEs, FNO, DeepONet)\nExposure to digital twin or closed-loop workflows: model calibration, active learning, Bayesian optimization\nDomain knowledge in electrochemistry, formulations, superconductors, or materials science\nAbout LILA\nLila 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.\nLILA 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.\nGuided 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.\nWe’re All In\nLila 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.\nInformation you provide during your application process will be handled in accordance with our Candidate Privacy Policy.\nA Note to Agencies\nLila 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 internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.","description_format":"text","description_chars":4318,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Materials Science & Nanotechnology","Laboratory & Pharmaceutical Robotics","AI Research Labs","AI for Science"],"lifecycle":[{"event":"open","at":"2026-10-30T20:32:27Z"}],"visa":[{"country":"US","licensed_sponsor":true,"adverts_offering_sponsorship_24m":0,"sanctioned_now":false,"evidence":"H-1B filings in 12 months: 29","filings_12m":29,"filings_prev_12m":4,"green_card_filings_12m":0,"median_offered_wage_usd":157500,"route":null,"cap_exempt":false,"checked_at":"2026-11-09T07:32:21+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)"],"filings_for_role_12m":0}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":9,"expected_fill_days":85,"reasons":["conf:0","velocity","win:early","comp:brand"],"computed_at":"2026-11-09T06:03:00Z"},"pay":null,"html_url":"https://alion.io/job/lila-sciences-co-op-ai-driven-equation-discovery","json_url":"https://alion.io/job/lila-sciences-co-op-ai-driven-equation-discovery.json","meta":{"generated_at":"2026-11-09T19:46:08Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":6025,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-10T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":65163},"rest":"https://alion.io/mcp/rest/get_company?id=65163"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Flila-sciences-co-op-ai-driven-equation-discovery"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":2,"usd":0.2},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Flila-sciences-co-op-ai-driven-equation-discovery"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Flila-sciences-co-op-ai-driven-equation-discovery"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/lila-sciences-co-op-ai-driven-equation-discovery\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Flila-sciences-co-op-ai-driven-equation-discovery"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3545172}},{"tool":"search_jobs","arguments":{"company":"lila.ai","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3545172},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. Docs: https://alion.io/developers"}}