Data Science / Optimization Intern at Applied… · Santa…

Summary: Applied Materials is a global leader in materials engineering solutions for semiconductor and display manufacturing. They are seeking a Data Science / Optimization Intern to work on AI-driven optimization problems using machine learning and physics-informed models, with mentorship from experienced engineers. Responsibilities: - Develop and apply machine learning models for surrogate modeling of physical and engineering systems - Support optimization algorithms for recipe and hardware parameter tuning - Analyze simulation and experimental data to improve model accuracy and performance - Build Python-based workflows for model training, inference, and evaluation - Collaborate with engineers and scientists to translate engineering problems into data-driven models - Document methods and results and present findings to technical stakeholders Required Qualifications: - Currently pursuing a Bachelor's degree in: Computer Science, Data Science, Electrical, Mechanical, or Chemical Engineering, Applied Mathematics or a related technical field - Strong programming skills in Python - Understanding of machine learning fundamentals - Coursework or hands‑on experience in optimization, numerical methods, or scientific computing - Ability to work with data, debug models, and learn quickly Preferred Qualifications: - Exposure to optimization techniques (e.g., gradient‑based methods, Bayesian optimization) - Experience working with simulation or experimental data - Familiarity with NumPy, SciPy, scikit‑learn, or PyTorch - Interest in applied engineering or manufacturing problems Required Skills: Python, Machine Learning Fundamentals, Optimization Techniques, Numerical Methods, Scientific Computing, Data Analysis, Simulation Data Handling, Experimental Data Handling Benefits: Comprehensive benefits package, Participation in a bonus and a stock award program