Computational Materials Scientist at Radical AI

, California, United States -

Full Time

Start Date

Immediate

Expiry Date

14 Jun, 26

Salary

0.0

Posted On

16 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Materials Simulations, AI/ML Model Building, Ab-initio Calculations, DFT, Molecular Dynamics, Computational Modeling, Theory-based Modeling, Software Development, Data Aggregation, Data Generation, Machine Learning, AI-enabled Workflows, Computational Chemistry, Reaction Discovery, Semiconductor Integration, Materials Discovery

Industry

Chemical Manufacturing

Description

Radical AI 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. As a Computational Materials Scientist, you will be engaging in materials simulations and AI/ML model building for materials discovery, development, and characterization. Your expertise with ab-initio calculations, DFT, molecular dynamics, and other forms of computational and theory-based modeling will be crucial to our AI-driven discovery process. Special emphasis will be on techniques and software development to quantify the delta between bulk material properties and thin film, interfaces, and multi-stack material properties that drive semiconductor integration research and development. You will explore a range of properties from mechanical, electrical, and thermal to develop metrics for screening materials for different end commercial applications. 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 materials, 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. In addition, you will be expected to interact regularly with computational chemists focusing on precursor discovery as well as reaction discovery in gas phase and on surfaces. You want to not just live in your computer simulations but be exposed to the messy reality and the challenge of verifying your predictions with real data and be open to deep diving to understand why the results don’t agree and what to do better next time. We are looking for both a designer to develop core AI/ML and DFT workflows and potentially software as well as an application engineer to execute workflows at scale to help drive wet materials research and development. The journey to commercialization of new materials is long and windy. You must be patient, ready, and look forward to the twists and turns \n What We Offer Medical, dental, and vision insurance for you and your family, covered at 100% Mental health and wellness support Flexible PTO and 14+ company holidays per year 401K Work closely with a team on the cutting edge of AI research A mission: an opportunity to fundamentally change the way humanity makes progress through materials science discovery \n 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.

Responsibilities

The scientist will engage in materials simulations and AI/ML model building for discovery, development, and characterization, utilizing expertise in ab-initio calculations and DFT. Responsibilities include running AI-enabled computational workflows and interacting with computational chemists on precursor and reaction discovery.