# Co-Op, Bayesian Methods for Complex Decision Making at Lila Sciences - Company: Lila Sciences - Status: Open - Workplace: On-site - Location: Cambridge, MA USA; San Francisco, CA USA - Level: Junior - Discipline: AI & ML - Employment: Internship - Posted: 2026-10-30 - Skills: AI, Bayesian - Apply: https://job-boards.greenhouse.io/lilasciences/jobs/4469148009 ## Description Your Impact at LILA Lila Sciences builds AI systems that accelerate discovery across the physical and life sciences. Within Physical Sciences AI, we work with experimental teams to build autonomous discovery agents that decide which experiments Lila's AI Science Factories should run next. Real scientific campaigns rarely look like textbook optimization problems. A single campaign can mix large discrete choices (which components, which recipe) with continuous settings (amounts, temperatures, times), pursue several objectives under hard constraints, and draw on evidence from literature and characterization data. Every experiment costs real time and materials. Off-the-shelf methods often struggle here, and they ignore the domain structure that could guide the search. As a Bayesian Methods Co-Op, you will work alongside research scientists and engineers on a focused project within one broad question: how AI systems can make better experimental decisions. Depending on your background, that could mean building agents that choose the next experiment, testing when in-context learners can be trusted as decision-makers, or developing Bayesian strategies for tight experimental budgets. Your methods will be tested against live campaigns. What You'll Be Building • Design and benchmark experiment-selection strategies that balance exploration and exploitation under realistic budgets • Build autonomous discovery agents that propose the next experiment from surrogate models • Develop in-context learning approaches inspired by Bayesian inference, evaluating calibration and robustness • More Lila Sciences roles: https://deviantjobs.com/companies/lila-sciences