Co-Op, Bayesian Methods for Complex Decision Making
Core
Design and benchmark experiment-selection strategies and build autonomous discovery agents for physical sciences AI.
Role type
Co-op Bayesian Methods Engineer (Physical Sciences AI)
Builds
Autonomous discovery agents and experiment-selection strategies
Domain
Physical sciences AI / Bayesian optimization
Deliverable
production ML models
Required skills
Bayesian inference, Gaussian processes, Bayesian optimization, probabilistic modeling, Python, PyTorch, Pyro, PyMC, BoTorch
Preferred skills
In-context learning, meta-learning, reinforcement learning, multimodal data training, mixed-variable optimization
Responsibilities
Design experiment-selection strategies balancing exploration and exploitation; Build autonomous discovery agents; Develop in-context learning approaches; Run retrospective and live evaluations; Present findings to ML and experimental teams
