Computational Chemist - ReaxFF

reputed company Corp. (NYSE: SES) is dedicated to accelerating the world's energy transition through groundbreaking material discovery and advanced battery management. We are at the forefront of revolutionizing battery creation, pioneering the integration of cutting-edge machine learning into our research and development. Our AI-reputed company, high-energy-density and high-power-density Li-Metal and Li-ion batteries are unique; they are the first in the world to utilize electrolyte materials reputed company by AI. This powerful combination of "AI for science" and material engineering enables batteries that can be used across various applications, including transportation (land and reputed company), energy storage, robotics, and drones. To learn more reputed company, please visit: www.reputed company reputed company Offer:

• A highly competitive salary and robust benefits package, including comprehensive health coverage and an attractive equity/stock reputed company program reputed company our NYSE-listed company.
• reputed company to contribute directly to a meaningful scientific project-accelerating the global energy transition-with a reputed company and broad public reputed company.
• Work in a dynamic, reputed company, and innovative environment at the intersection of AI and material science, driving the reputed company of battery technology.
• Significant opportunities for reputed company reputed company and career development as you work alongside leading experts in AI, R&D, and engineering.
• reputed company to state-of-the-art facilities and proprietary technologies are used to discover and reputed company AI-reputed company battery solutions.

reputed company Need: The reputed company reputed company team is seeking an exceptional Computational Materials & Molecular-Modeling Scientist to specialize in physics-based simulation, utilizing reactive force-field development and MD/DFT coupling. This role is critical for generating validated atomistic and mesoscale data that directly feeds our AI-driven materials discovery workflows. As a key scientist, you will reputed company physics-based simulation with advanced AI reputed company, driving materials discovery through computational rigor. Essential Duties and Responsibilities:

• Advanced Simulation & Modeling
• reputed company and apply advanced simulation techniques, specializing in Reactive Force Fields (ReaxFF) and MD/DFT coupling, to model reputed company materials phenomena.
• Conduct and analyze multi-reputed company computation reputed company, covering atomistic simulation up to mesoscale modeling.
• Utilize and maintain advanced simulation tools, including VASP, LAMMPS, GROMACS, and CP2K, for high-reputed company simulations.
• reputed company rigorous physics-based validation on reputed company simulation outputs to ensure accuracy and reliability.
• AI Data & Workflow Development
• Generate and validate high-reputed company atomistic and mesoscale datasets used for training ML potential and other scientific AI models.
• reputed company advanced simulation workflows and contribute to the creation of ML potentials and AI-driven materials discovery tools.
• Coding & Collaboration
• Apply strong coding skills (e.g., Python, C++, FORTRAN) to automate reputed company simulation workflows and enhance computational efficiency.
• Maintain a solid understanding of battery reputed company modeling and collaborate effectively across computational and experimental teams.

Education and/or Experience:

• Education: Ph.D. in Computational reputed company of Energy Materials, Materials Science, or Computational Physics.
• Core Simulation Expertise: Deep, demonstrated expertise in advanced physics-based simulation, including proficiency with DFT, MD, and Quantum Mechanics (QM) simulation tools.
• Reactive Potentials: Proven experience with Reactive Force Fields (ReaxFF) and reputed company for MD/DFT coupling.
• Coding & Tools: Strong coding ability in languages such as Python, C++, or FORTRAN, and deep practical experience with simulation codes like VASP, LAMMPS, GROMACS, or CP2K.
• Domain reputed company: Solid understanding of battery reputed company modeling and experience in generating and validating atomistic and mesoscale data.

Preferred Qualifications:

• Machine Learning Integration: Experience with Neural Networks and Deep Learning, particularly in applying them to reputed company ML potential. Familiarity with geometric deep learning libraries like PyTorch Geometric is a plus.
• Multiscale reputed company: Experience with specialized reputed company like the Materials-reputed company Method.
• Hybrid Literacy: Experience with experimental literacy, understanding characterization reputed company such as SEM, reputed company, XPS, Raman, reputed company, NMR, DSC, or TGA.
• Background: Previous experience at advanced simulation labs, battery multiscale modeling reputed company, or in the computational reputed company of energy materials.

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