Applied Materials is looking for a computational scientist to help create the next generation semiconductor material processes and reactors via semiconductor process modeling. The semiconductor process modeling expert will develop and utilize models which predict on wafer performance during the many process steps in a semiconductor fabrication process. As the member of a larger Computer Aided Engineering (CAE) team you will play a key role in the development of Applied Materials chambers and processes. Statement of Responsibilities and Duties:
- Develop computational models of chambers and processes being developed at Applied Materials
- Apply developed models using process recipes to predict on wafer performance. On wafer performance can include wafer to wafer repeatability, across wafer process uniformity, achieving a desired profile shape, step coverage, material change, etc.
- Use modeling to understand and propose new unit processes, new process sequences, new chemistries, solve chamber design issues, propose new chamber designs, and trouble shoot current production issues.
- Develop and maintain semiconductor process modeling scientific software through algorithm development, implementation of new capabilities, identifying and fixing bugs.
- Maintain awareness of technical literature, publish research results in peer-reviewed scientific or technical journals and present results at external conferences, seminars and/or technical meetings.
- Perform other duties as assigned.
- PhD in physics, electrical engineering, chemistry, or related field, or the equivalent combination of education and related experience.
- Knowledge of semiconductor processes such as etch (ex: plasma, wet), deposition (ex: atomic layer deposition, chemical vapor deposition, physical vapor deposition), epitaxy, electroplating, thermal, doping, and other surface modification process (ex: nitridation, oxidation).
- Knowledge of surface chemistry
- Knowledge of low temperature plasmas and reactive flows
- Scientific software development experience including modern code best practices, version control, test-driven development, algorithm development, parallelization techniques.
- Coding proficiency in languages such as C/C++, Fortran77/90, Python, R, or similar languages
- Familiarity with techniques such as molecular dynamics, particle-in-cell, and direct simulation Monte Carlo
- Experience with data analysis, mathematical statistical modeling, machine learning, optimization, calculus, linear algebra.
- Some deep learning statistical library experience in python (e.g., pytorch, tensorflow, keras, scikit-learn, statsmodels, etc.) or R (e.g., caret, randomForest, e1071, rpart, glmnet, etc.) a plus.
- Interacts effectively with a broad range of colleagues such as hardware engineers, process engineers, program managers, and computational scientists.
- Demonstrates depth and/or breadth of expertise in own specialized discipline or field
- Interprets internal/external business challenges and recommends best practices to improve products, processes or services
- May lead functional teams or projects with moderate resource requirements, risk, and/or complexity
- Leads others to solve complex problems; uses sophisticated analytical thought to exercise judgment and identify innovative solutions
- Impacts the achievement of customer, operational, project or service objectives; work is guided by functional policies
- Communicates difficult concepts and negotiates with others to adopt a different point of view
Bachelor's Degree Skills Certifications: Languages: Years of Experience:
7 - 10 Years Work Experience: Additional Information Travel:
No Relocation Eligible:
Applied Materials is an Equal Opportunity Employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.