Technical Project Lead - Battery Simulation

Role Summary: This is a technical leadership position responsible for building and leading our computational research capabilities from the ground up. The role combines deep technical expertise in battery modelling with team leadership and strategic thinking to create a multi-scale simulation platform that will transform how the company designs and optimises battery technology.

Success in this position looks like: Successfully architecting and deploying a comprehensive modelling platform that integrates quantum to manufacturing-scale simulations, building and mentoring a high-performing team of 3-5 researchers, reducing R&D development cycles by 10x through predictive design capabilities, and establishing validated computational workflows that directly inform production decisions.

Organisational fit: This role reports directly to the CTO and serves as the technical foundation for our data-driven approach to battery innovation. The position bridges the gap between fundamental research and manufacturing optimisation, making it central to the company's mission of revolutionising battery technology through computational innovation.

Responsibilities:

• Architect and design a multi-scale simulation framework that seamlessly integrates quantum mechanics (DFT), molecular dynamics, mesoscale, and continuum models using modern integration protocols
• Build, hire, and mentor a world-class computational battery research team of 3-5 scientists, establishing technical standards and fostering innovation
• Develop comprehensive physics-based models for battery degradation mechanisms including SEI formation, lithium plating, and thermal effects
• Create robust APIs and integration interfaces connecting simulation platforms with experimental data collection systems
• Establish and validate computational predictions through systematic comparison with experimental data from manufacturing facilities
• Drive breakthrough research by coupling plasma deposition physics with electrochemical modelling for novel material discovery
• Transform organisational R&D methodology from trial-and-error approaches to predictive design workflows

Qualifications:

Education: Masters in Computational Materials Science, Chemical Engineering, or Physics, or Master's degree with 5+ years of relevant industry experience

Technical Expertise: Proven experience in battery modeling including electrochemistry, transport phenomena, and degradation mechanisms

Software Proficiency: Hands-on experience with at least two of the following: COMSOL Multiphysics, LAMMPS, VASP, or Quantum ESPRESSO

Programming Skills: Strong Python programming capabilities and scientific computing experience

Systems Experience: Demonstrated track record of building and deploying production-scale simulation systems

Leadership Experience: Experience managing technical teams or leading complex multi-stakeholder projects

Preferred Qualifications: Knowledge of plasma physics and surface chemistry, experience with Model Context Protocol (MCP) or similar integration frameworks, machine learning experience for surrogate model development, published research in battery simulation or computational electrochemistry, and startup or high-growth environment experience

Communication Skills: Ability to present complex technical concepts to diverse stakeholders and collaborate effectively across interdisciplinary teams