Co-op, Machine Learning for Digital Twins
Lila Sciencesabout 5 hours ago
Cambridge, MA, USAIntern / Entry Level
H1B Sponsor
Responsibilities
- Contribute to ML models for scientific and experimental systems focused on a specific digital twin sub-problem.
- Build and train surrogate, operator-learning, or physics-informed models using experimental and simulation data.
- Calibrate models, quantify uncertainty, and validate against data from active experimental campaigns.
- Frame scientific questions as concrete ML tasks with clear datasets and evaluation criteria.
- Document findings and share results through write-ups and presentations.
Requirements
- Pursuing a Master's or PhD in Machine Learning, Computer Science, Applied Mathematics, Physics, or related fields.
- Strong programming skills in Python and experience with ML frameworks like PyTorch, JAX, or TensorFlow.
- Experience applying machine learning to scientific or experimental systems.
- Familiarity with neural operators, operator learning, and scientific computing.
- Ability to convert open-ended scientific questions into concrete ML tasks.
- Solid foundation in model training, validation, and performance evaluation.
- Comfort working with messy or heterogeneous scientific datasets.
- Clear communication skills and interest in cross-departmental collaboration.