Computational Materials Scientist

Key Responsibilities:\n\n * Chemistry and materials design for screening and optimization applications with special emphasis on at least one of the following areas: polymeric materials formation and viscosity, precursor design for purity of deposition, ALD and CVD reactions of molecules in gas phase and on surfaces\n * Recommend atomic-scale changes to structure and/or processing conditions to influence observed properties\n * Scope the diverse cutting-edge materials and chemistry discovery tools on the market for potential future value and prioritize what methods warrant further exploration\n * Evaluate a variety of MLIP\u2019s for validation required property prediction and potential extend to fine-tuning of MLIP\u2019s for increased accuracy.\n * Explore various molecule and chemistry focused featurization and ML to determine which can add practical value to drive R\u0026D\n * Hypothesize and test mechanisms to determine the root-cause of observed behavior\n * Work effectively with external vendor software providers in testing new features and functionality of new products\n * Work effectively with internal multi-disciplinary teams of experimentalists, modelers, and computing infrastructure support teams\n * Demonstrate analytical and engineering judgement to scope and assess the appropriate level of model required\n * Proactively validate/correlate results with real world data to improve models\n * Present complex in-depth technical material in a concise manner\n * Advocate for the power of modeling while also communicating limitations\n * Serve as a business unit chemistry, materials, or physics expert\n * Provide parameters, inputs, and/or guidance for higher-level process, feature, and reactor models\n\n\n\nBackground/Skills:\n\n * Extensive experience with First Principles/Ab-initio/Density Functional Theory (local orbital and plane wave), Molecular Dynamics, and/or Monte Carlo methods\n * Extensive experience with machine learning interatomic potentials both at the training stage and inference stage. Experience with both universal and focused approaches a plus.\n * Experience with polymer modeling workflows from polymer structure creation including branching and cross-linking to property prediction especially with a focus on non C-based polymers\n * Experience with ML/AI tools (PyTorch, scikitLearn, Chemprop, SMILES, RDKit, LLM, GNN, etc.), scripting (python, Linux), programming (C, Fortran, etc.), and databases (SQL, MongoDB, etc.)\n * Knowledge of informatics, artificial intelligence, machine learning, and data science approaches\n\n\n\n## Qualifications\n\n### Education:\n\nBachelor\u0027s Degree\n\n### Skills\n\n### Certifications:\n\n### Languages:\n\n### Years of Experience:\n\n7 - 10 Years\n\n### Work Experience:\n\n## Additional Information\n\n### \n\n### Shift:\n\nDay (India)\n\n### \n\n### Travel:\n\nYes, 10% of the Time\n\n### \n\n### Relocation Eligible:\n\nYes\n\n### Referral Payment Plan:\n\nEmployee Referral (Standard)\n\nApplied 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. \n