Engineering Intern 1
Core
Internship focused on Explainable AI and Bayesian Optimization for probabilistic surrogate models in semiconductor process development.
Role type
Research intern (Explainable AI / Bayesian Optimization)
Builds
Interpretation methods and post-hoc explanations for Bayesian surrogate models and optimization pipelines
Domain
Semiconductors / Machine Learning
Deliverable
research
Required skills
Statistical machine learning, Probabilistic modeling, Explainable AI, Bayesian Optimization, Gaussian Processes, Kernel methods, Uncertainty quantification, Python programming, PyTorch, GPyTorch, BoTorch, NumPy, Pandas, Visualization libraries, Correlation analysis, Feature attribution, Sensitivity analysis
Preferred skills
Synthetic benchmark functions, Causal reasoning, Spatial data, Structured outputs
Responsibilities
Explore Explainable AI literature and develop methods for interpreting Bayesian surrogate models, Develop methods to interpret modeled correlations and compare with known data properties, Create post-hoc explanations for BO recommended solutions, Implement reproducible experiments on synthetic and real data, Investigate interpretable representations of correlation and latent structure, Develop local post-hoc explanation methods (attribution, counterfactuals, sensitivity analysis), Define and validate criteria for explanation fidelity and stability, Create visualizations and technical documentation
Seniority
Intern
