Location: London, UK or Remote

Type: Full-time

About Us

We are a cutting-edge startup dedicated to accelerating the development of battery materials through computational chemistry, physics simulations, and machine learning. At our core, we value innovation, collaboration, and a commitment to driving the future of sustainable energy solutions.

The Problem

Discovering new sustainable materials is crucial for our planet’s future. However, it currently takes up to 20 years and costs $10-100m to commercialize a new material with specific properties. Bringing a new battery material from idea to commercialization requires on average 14,000 experiments. Most teams still rely on trial-and-error experimentation during their materials R&D because they lack the expertise or resources to calculate materials properties and simulate materials behaviors with computational methods.

Our Solution

We are building an AI-powered platform that accelerates the development process of new sustainable battery materials. The platform enables R&D teams to run no-code simulations on the cloud, calculate materials properties and predict in-device performance to complement and accelerate their physical experiments. By 2026, we aim to couple this platform with robotic laboratories in order to give R&D teams the ability to run experiments remotely such as solid-state synthesis, materials characterization, and battery testing. 

State of Progress

Our vision is to pave the way for a new era of materials development, by making the development process of every material available from just a laptop. We are a team of 6 and have recently completed building our minimal viable product.

Job Description

We are in search of a Battery Computational Scientist Lead with expertise in Density Functional Theory (DFT), Molecular Dynamics (MD), and/or Machine Learning (ML) to join our dynamic team. The chosen candidate will hold a pivotal role in advancing our computational models for battery materials.

Key Responsibilities

• Develop DFT, MD, and ML pipelines for the development of battery materials.
• Create and implement machine learning models to optimize battery performance.
• Collaborate closely with experimental teams to validate computational models, fostering our interdisciplinary approach.
• Work in tandem with our software engineering teams to integrate your results into our platform, contributing to the realization of our vision.

Qualifications

• PhD in Materials Science, Chemistry, Physics, or a related field.
• Proven experience in DFT, MD, and/or ML as applied to battery materials.
• Proficiency in Python, Shell scripting, and a deep understanding of quantum chemistry software such as VASP & Quantum Espresso.

Company benefits

• 💰Competitive salary and equity options
• 🧑‍🤝‍🧑Opportunity to work on groundbreaking technology with a team of visionary innovators
• 📈Collaborative and innovative work environment that fosters professional growth
• 🌍 Genuine flexibility in how and where you work and a commitment to work-life balance
• 🏝️ 25 days' holiday (+ bank holidays)
• 🏕️ Annual team off-sites
• 🏢 Modern and centrally located office in London
• 💝 We’re still deciding our full benefits package and we’re looking forward to working with our early employees to figure out what matters the most
• 💸 Pension plan

Company values

• 🚀 Ambition - we're unashamedly ambitious about what we’re building
• 👂 Humility - we believe you never stop learning
• 🤝🏽 Customer-Centric - we build our product around our customers’ needs
• 🔥 Empowerment - we are dedicated to providing the support you need to excel in your role

How to Apply

To join our team, please send your CV and cover letter to [email protected]. 

We encourage candidates from diverse backgrounds and experiences to apply.