Radical AI
Computational Chemist/Material Scientist - Metal Alloys
Radical AI, New York, New York, us, 10261
Radical AI, Inc. is an artificial intelligence company that is accelerating scientific research & development. We are at the forefront of innovation in the field of materials R&D, a critical driver for advancing our most cutting-edge industries and shaping the future. Breaking away from the traditionally slow and costly R&D process, Radical AI leverages artificial intelligence and machine learning to pioneer generative materials science. This innovative field blends AI, engineering, and materials science, revolutionizing how materials are created and discovered. Radical AI's approach speeds up R&D and addresses global challenges, setting new benchmarks in technology and sustainability.
The Opportunity As a Computational Materials Scientist, you will be engaging in critical simulations and modeling for materials discovery, development, and characterization. Your expertise with ab-initio calculations, DFT, and other forms of computational and theory-based modeling will be crucial to our AI-driven discovery process. You will work with leading AI scientists who depend on you to assist in data aggregation, data generation, materials simulation and model development. You will draw on a robust background in computational chemistry, software development, and machine learning. You will be responsible for running AI-enabled computational workflows for materials discovery, serving as a critical resource to the ML and materials research teams.
About you
PhD degree in Chemistry, Materials Science, Computational Chemistry, Chemical Engineering, or another related subject.
Strong research experience (e.g., evidenced by publication record), including experience in computational modeling, utilizing ab-initio methods, and coarse-graining potentials for multiscale simulations of atomistic systems.
Understanding of the fundamental mechanics of metals and how to model them computationally.
Experience running high-throughput DFT.
Experience with interatomic potentials.
Chemistry software development experience (preferably public on e.g. GitHub, please share links to high impact pull request).
Experience coding in Python or other similar languages.
Pluses
Running high-throughput DFT workflows at the order of 5,000+ concurrent jobs.
Prior experience in transitioning AI + computational research into production environments.
Experience with additional ICME approaches (e.g., mechanistic structure-property modeling, Phase Field, CALPHAD, Atomistics, Molecular statics/dynamics, etc.).
Experience with FEM software tools (e.g., ANSYS, ABAQUS, MOOSE, PRISMS).
Experience with metal additive manufacturing techniques.
Salary Description Competitive salary + Equity + Benefits; base pay offered may vary depending on job-related knowledge, skills, and experience.
Disclosure Radical AI is committed to equal employment opportunity regardless of race, color, ancestry, national origin, religion, sex, age, sexual orientation, gender identity and expression, marital status, disability, or veteran status.
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The Opportunity As a Computational Materials Scientist, you will be engaging in critical simulations and modeling for materials discovery, development, and characterization. Your expertise with ab-initio calculations, DFT, and other forms of computational and theory-based modeling will be crucial to our AI-driven discovery process. You will work with leading AI scientists who depend on you to assist in data aggregation, data generation, materials simulation and model development. You will draw on a robust background in computational chemistry, software development, and machine learning. You will be responsible for running AI-enabled computational workflows for materials discovery, serving as a critical resource to the ML and materials research teams.
About you
PhD degree in Chemistry, Materials Science, Computational Chemistry, Chemical Engineering, or another related subject.
Strong research experience (e.g., evidenced by publication record), including experience in computational modeling, utilizing ab-initio methods, and coarse-graining potentials for multiscale simulations of atomistic systems.
Understanding of the fundamental mechanics of metals and how to model them computationally.
Experience running high-throughput DFT.
Experience with interatomic potentials.
Chemistry software development experience (preferably public on e.g. GitHub, please share links to high impact pull request).
Experience coding in Python or other similar languages.
Pluses
Running high-throughput DFT workflows at the order of 5,000+ concurrent jobs.
Prior experience in transitioning AI + computational research into production environments.
Experience with additional ICME approaches (e.g., mechanistic structure-property modeling, Phase Field, CALPHAD, Atomistics, Molecular statics/dynamics, etc.).
Experience with FEM software tools (e.g., ANSYS, ABAQUS, MOOSE, PRISMS).
Experience with metal additive manufacturing techniques.
Salary Description Competitive salary + Equity + Benefits; base pay offered may vary depending on job-related knowledge, skills, and experience.
Disclosure Radical AI is committed to equal employment opportunity regardless of race, color, ancestry, national origin, religion, sex, age, sexual orientation, gender identity and expression, marital status, disability, or veteran status.
#J-18808-Ljbffr