We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company
Job Summary
We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company.
The role focuses on developing and applying machine learning and optimization techniques using physics‑informed and data‑driven surrogate models, with mentorship and training provided by experienced engineers and data scientists.
At Applied Materials, we care about the health and wellbeing of our employees and provide programs that encourage personal and professional growth.
Matching Summary
We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company.
Skills & Requirements
Must-have
machine learning model development
optimization algorithm support
Python programming skills
data analysis and debugging
surrogate modeling of physical systems
Nice-to-have
experience with NumPy and SciPy
familiarity with scikit-learn or PyTorch
exposure to Bayesian optimization
interest in applied engineering problems
collaboration with engineers and scientists
Key Requirements
Currently pursuing Bachelor’s degree in related technical field
Strong programming skills in Python
Coursework or experience in optimization or scientific computing