
Computational Materials Scientist, Atomic Layer Processing and Chemical Reactivity
Quick overview
Job description
Schrödinger seeks a Computational Materials Scientist in Atomic Layer Processing and Chemical Reactivity to join us in our mission to improve human health and quality of life through the development, distribution, and application of advanced computational methods.
As a member of our Materials Science Modeling Services team, you’ll work closely with colleagues to help customers benefit from our computational tools in solving problems in industrial research and development.
Who will love this job:
- A computational chemistry expert who has had hands-on experience with studying real-world materials science problems at the atomic level, especially with periodic density functional theory (DFT)
- A scientist who has engaged with research questions in surface chemistry and molecular reactivity
- An excellent communicator and team player who can translate complex scientific concepts for both technical and non-technical stakeholders
- A detail-oriented scientist eager to work on diverse projects with industrial partners
- An innovative and creative thinker who experiments with new tools and techniques
What you’ll do:
- Perform simulations-focused research projects using Schrödinger tools
- Execute and quickly analyze thousands of simulations
- Collaborate with cross-functional teams to identify and implement atomic simulation solutions for semiconductor and other industries
- Efficiently run multiple projects, meet deadlines and manage stakeholders
- Present technical results in internal and external meetings
- Contribute to scientific publications and research projects
What you should have:
- PhD in computational materials science, or in related fields of chemistry, physics or engineering
- Evidence of deep level of expertise running periodic DFT code
- At least three years of experience modeling surface reactivity, such as gas-surface interactions or the mechanism of thin-film deposition and etch (ALD/CVD)
- Hands-on experience with advanced techniques for computing chemical kinetics, reaction networks, and complex mechanisms
- Familiarity with semi-empirical methods or Machine Learning Interatomic Potentials, along with their use for molecular dynamics (MD)
- Proven expertise in launching and analyzing large scale simulation projects
- Use of high-performance computing (HPC) environments and Linux operating systems
- Proven research track record of publications in the computational modeling field
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