Website:
agratas.com
Job details:
About Agratas
Agratas is a wholly owned subsidiary of Tata Sons. We design, develop and manufacture high-quality, high-performance, sustainable batteries applied to multiple use cases in the mobility and energy sectors, to match our customers’ requirements.
Agratas is a scale-up business with a start-up mentality, driven by our pursuit of green growth and technological progress.
We develop next-generation battery technologies at our state-of-the-art R&D Innovation Hubs in India and the UK.
The Opportunity
The high level purpose of the role includes:
- Business Expertise: Should possess a holistic view of the organization, understanding the interconnection between R&D (pack design, pack engineering, process engineering) and manufacturing. Facilitate collaboration with other R&D functionals to drive innovation and commercial success
- Problem Solving: Problems are often at cutting edge of science and technology, requiring creative solutions and ability to navigate uncertainty. Challenges in access to necessary infra, coordinating multiple research streams and aligning R&D efforts with broader company goals.
- Nature & Area of Impact: Greatly responsible in providing insights and support through simulations to cell development and process/product engineering teams. Data driven approach that can provide cost-efficiency and process optimisation that will lead to overall business impact
Key Accountabilities and Responsibilities
- Design and execute DFT calculations to predict and explain – bulk and surface properties, interfacial phenomena, diffusion / transport properties of battery materials
- Perform classical molecular dynamics and/or ab-initio molecular dynamics (AIMD) to study solvation structure, ion pairing, SEI/CEI formation, decomposition pathways, interphase stability, temperature dependent behaviour and mechanical stability of materials.
- To work closely with R&D teams to support materials screening and down-selection. Provide physics-based inputs to battery cell performance and degradation models
- Translate simulation results into actionable guidance for materials design, processing and performance improvement
Knowledge, Skills and Experience
Essential
- Deep hands-on expertise in first-principles simulations including Density Functional Theory (DFT), Molecular Dynamics (MD).
- Strong experience in at least one DFT simulation tool (Gaussian, Quantum Espresso, VASP) and MD tool (LAMMPS, Gromacs). Force-field selection/validation and trajectory analysis
- Solid understanding of battery materials chemistry including electrodes, electrolyte, interfaces, SEI/CEI chemistry and degradation mechanisms
- Ability to connect atomistic-scale insights to macroscopic performance trends
Desired
- Knowledge of the state-of-the-art research in next-gen battery materials, advanced electrolytes etc
- Experience applying AI/ML to materials discovery and screening and accelerating DFT/MD workflows
Role Specific Qualifications/Certifications
- PhD in Computational Chemistry / Materials Science / Physics or related discipline
- At least 3+ years of post-PhD experience in quantum simulations
Demonstrated track record of solving materials problems using DFT + MD and communicating outcomes effectively (publications, patents, or industry deliverables)
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