Computational Chemist/Physicist

About Exoben:

Exoben Inc. is at the forefront of clean energy innovation, specializing in the development of advanced lithium and sodium battery systems for electric vehicles (EVs), renewable energy storage, and cutting-edge applications. As we strive to push the boundaries of energy storage technology, computational modeling plays a critical role in guiding experimental design and optimizing material performance. Our team of world-class engineers, chemists, and physicists is dedicated to revolutionizing energy storage and enabling a sustainable future. Join us in transforming the energy industry through innovative computational methods.

Job Description:

We are seeking a talented and highly experienced Computational Chemist/Physicist to join our research and development team. In this role, you will focus on computational modeling and simulations of new materials, chemical reactions, and battery systems to predict performance and guide experimental design. Your work will be instrumental in optimizing the behavior of materials, enhancing the energy density, efficiency, and safety of our battery technologies. You will collaborate closely with experimentalists, material scientists, and engineers to provide insights that accelerate the discovery and development of next-generation battery materials.

This is a unique opportunity to shape the future of energy storage by leveraging your expertise in computational modeling to drive real-world innovation in battery technology.

Key Responsibilities:

• Computational Modeling of Materials: Use advanced computational techniques to model and simulate the behavior of battery materials, including electrodes, electrolytes, and solid-state interfaces. Predict material properties such as ionic conductivity, chemical stability, and energy density under various operating conditions.
• Simulation of Chemical Reactions: Simulate and analyze chemical reactions within battery systems, including charge/discharge cycles, solid-electrolyte interphase (SEI) formation, and material degradation. Provide insights into optimizing chemical processes to improve battery performance and longevity.
• Multiscale Simulations: Conduct multiscale simulations that bridge atomistic, molecular, and continuum-level models to study material properties and battery behavior. Utilize techniques such as density functional theory (DFT), molecular dynamics (MD), and continuum mechanics to predict the performance of materials across different scales.
• Battery Performance Prediction: Use computational models to predict the performance of battery systems, including energy density, power output, thermal behavior, and safety. Provide recommendations to optimize the design of battery cells, modules, and packs based on simulation results.
• Electrochemical Process Optimization: Collaborate with electrochemists and material scientists to simulate and optimize electrochemical processes, focusing on improving the charge/discharge efficiency, cycle life, and overall energy storage capacity of battery systems.
• Materials Discovery & Design: Contribute to the discovery and design of new battery materials by simulating material structures and predicting their properties before synthesis. Identify promising candidates for high-performance cathodes, anodes, and solid-state electrolytes.
• Interface Engineering: Model and simulate the interfaces between different battery components (e.g., electrode-electrolyte interfaces) to understand how they affect battery performance. Work on reducing interfacial resistance and improving material compatibility for better energy transfer and stability.
• Data-Driven Insights: Analyze large datasets from simulations and experiments to identify trends, correlations, and performance indicators. Use machine learning and statistical methods to enhance material prediction models and accelerate discovery.
• Collaborative Research: Work closely with experimentalists and engineers to validate computational predictions through laboratory experiments. Provide feedback on experimental designs and interpret results to refine computational models.
• Simulation Software & Tools: Develop, maintain, and improve computational tools and workflows for battery simulations. Use software such as VASP, Quantum ESPRESSO, LAMMPS, GROMACS, COMSOL, and other relevant platforms to run simulations and analyze results.
• Project Management: Lead or contribute to computational research projects, managing project timelines, resource allocation, and deliverables. Coordinate with cross-functional teams to ensure project goals are met on time and within budget.
• Documentation & Reporting: Prepare comprehensive technical reports, presentations, and research papers on computational findings. Share results with internal teams, stakeholders, and external collaborators. Contribute to patents and publications related to new material discoveries.

Qualifications:

• Educational Background: PhD in Computational Chemistry, Computational Physics, Materials Science, or a related field with a specialization in computational modeling of materials and energy storage systems.
• Experience: 6+ years of experience in computational research, particularly in the context of energy storage systems, battery technology, or material design. Experience in multiscale modeling and simulations for real-world applications is preferred.
• Technical Expertise: Proficiency in advanced computational techniques such as density functional theory (DFT), molecular dynamics (MD), Monte Carlo simulations, and continuum mechanics. Experience in simulating materials relevant to battery technology, such as electrodes, electrolytes, and interfacial materials.
• Simulation Software Skills: Hands-on experience with simulation tools such as VASP, Quantum ESPRESSO, LAMMPS, GROMACS, COMSOL, or similar platforms for modeling atomic, molecular, and macroscopic systems.
• Battery Knowledge: Strong understanding of electrochemical processes, material degradation mechanisms, and the structure-property relationships of battery components. Experience with modeling solid-state batteries, lithium-ion batteries, or sodium-ion batteries is a plus.
• Data Analysis & Machine Learning: Proficiency in analyzing large datasets from simulations and experiments. Familiarity with machine learning techniques and statistical methods to enhance computational models and material predictions.
• Problem-Solving Skills: Strong analytical and problem-solving skills, with the ability to troubleshoot complex simulation challenges and propose effective solutions for improving battery performance.
• Collaboration & Communication: Excellent interpersonal and communication skills, with the ability to work effectively in multidisciplinary teams and present complex computational findings to both technical and non-technical audiences.
• Project Management: Proven experience managing research projects, including planning, execution, and reporting. Ability to balance multiple projects and deliverables in a fast-paced environment.

Preferred Qualifications:

• Postdoctoral Experience: Postdoctoral research in computational chemistry, physics, or materials science, with a focus on energy storage materials or battery technology.
• Industry Experience: Experience working in the energy storage or battery technology industry, with a focus on applying computational models to accelerate the development of commercial battery systems.
• Machine Learning & AI: Experience applying machine learning and artificial intelligence to material discovery, data analysis, or optimization of chemical processes.
• Advanced Simulations: Expertise in advanced simulations of solid-state battery materials, interfaces, and electrochemical processes, with a track record of publishing research in peer-reviewed journals.

What We Offer:

• Competitive Compensation: A competitive salary with a comprehensive benefits package, including health insurance, retirement plans, and performance-based bonuses.
• Career Growth: Opportunities for professional development and career advancement in a fast-growing and dynamic field. Access to cutting-edge technologies and state-of-the-art computational resources.
• Impactful Work: Contribute to groundbreaking projects that have a direct impact on the global clean energy transition. Play a key role in shaping the future of energy storage technologies.
• Collaborative Environment: Work in a highly collaborative and innovative environment that values creativity, scientific rigor, and teamwork. Engage with a diverse team of experts from multiple disciplines.
• Work-Life Balance: We support a healthy work-life balance and offer flexible working arrangements where applicable.

how to apply:

If you are passionate about computational modeling and energy storage, we encourage you to apply. Submit your resume and a cover letter via Indeed or through our website at www.exoben.com  detailing your experience in computational research, battery modeling, and material optimization.

Exoben Inc. is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Join Exoben and contribute to the future of energy storage by pioneering new materials and battery technologies through cutting-edge computational research!