Description

You will accelerate material discovery for semiconductor manufacturing using computational chemistry, AI, and machine learning.

This role is on-site.

Responsibilities

• Apply computational chemistry methods, including DFT and QM/MM, to solve complex material science problems.
• Develop and deploy machine learning and deep learning models, with a focus on graph neural networks.
• Manipulate chemical structure information and representations using cheminformatics tools like RDKit.
• Analyze chemical properties and reactivity to support data-driven decision-making in manufacturing.
• Visualize data and represent analytical findings to communicate results effectively.

Required Skills

• 5+ years of experience in data science or computational chemistry roles.
• Strong expertise in Density Functional Theory (DFT) and Quantum Mechanics/Molecular Mechanics (QM/MM).
• Proficient in Python programming for scientific computing and data analysis.
• Solid understanding of chemistry concepts, including structure, reactivity, and properties.
• Experience with chemical informatics and libraries such as RDKit.
• Knowledge of machine learning and deep learning frameworks, particularly graph neural networks.
• Ability to visualize data and present analytical insights clearly.
• Excellent communication skills with a desire to work in multidisciplinary teams.

Preferred Skills

• Some knowledge of semiconductor manufacturing processes.

Key Skills

Education

Any Gradute