Job Overview
Location
London, UK
Job Type
Full-time
Category
Software Engineering
Date Posted
April 1, 2026
Full Job Description
đź“‹ Description
- • As an Application Scientist specializing in Mesoscale/Coarse-Grained Force Fields at Cusp AI Ltd, you will play a pivotal role in translating cutting-edge AI models into actionable materials science breakthroughs by developing simulation frameworks that bridge molecular discovery with real-world industrial performance—directly enabling solutions for global challenges in energy, clean water, carbon capture, and next-generation computing.
- • You will lead technical delivery for 1-2 key client projects as the subject matter expert in mesoscale phenomena, designing and implementing novel coarse-graining strategies (particularly with Martini 3), refining force fields, and executing high-fidelity Molecular Dynamics and mesoscale simulations to validate AI-driven material candidates while translating partner challenges into precise technical requirements.
- • You will collaborate closely with CuspAI’s AI Research and Particle Simulation ML teams to integrate machine learning models into simulation workflows, act as the internal authority on mesoscale methods, and participate in cross-functional sprints to build scalable multi-scale materials discovery infrastructure across London, Cambridge, Amsterdam, or Berlin offices.
- • In this role, you will deepen your expertise at the intersection of AI and computational materials science, gain hands-on experience deploying ML-enhanced simulation pipelines in industrial settings, and contribute to scalable platforms that accelerate materials discovery from atomic to macroscopic scales—positioning you as a leader in the emerging field of AI-driven multi-scale modeling.
- • You will develop advanced technical communication and client engagement skills by working directly with global partners to define project scope, deliver insightful technical reports, and demonstrate the tangible value of CuspAI’s technology in solving complex materials challenges, all while operating in a mission-driven, inclusive environment focused on sustainable innovation.
🎯 Requirements
- • Deep expertise in parameterizing mesoscale coarse-grain force fields and extensive hands-on experience with mesoscale methods, particularly Martini 3.
- • Strong software engineering foundations with proficiency in Python and proven experience using MD simulation packages such as GROMACS or LAMMPS.
- • Demonstrated background in both Machine Learning (ML) and Molecular Dynamics (MD), with the ability to fluidly navigate and integrate concepts from both disciplines.
- • Excellent communication skills and proven ability to engage directly with external partners to understand complex materials challenges and define clear technical deliverables.
- • Genuine enthusiasm for enabling scientific breakthroughs in sustainable materials, energy, and computing through AI-driven simulation technologies.
🏖️ Benefits
- • Competitive salary plus equity package, giving you direct ownership in the company’s success.
- • 28 days of annual leave to support work-life balance and sustained productivity.
- • Professional development budget for attending scientific conferences, technical training, and skill advancement.
- • Opportunity to work at the forefront of AI-driven scientific discovery alongside world-leading researchers in AI, chemistry, and engineering.
- • Direct impact on advancing materials science through scalable, multi-scale simulation technologies applied to real-world industrial problems.
- • Collaborative, inclusive culture that bridges AI research, computational chemistry, and experimental science across international hubs.
Skills & Technologies
About Cusp AI Ltd
Cusp AI is a Cambridge-based startup applying generative artificial intelligence and deep learning to the discovery and design of next-generation materials for carbon capture, hydrogen storage and other clean-energy applications. The company combines physics-informed models, molecular simulation and high-throughput cloud computing to predict and optimize porous frameworks such as metal-organic frameworks and covalent organic frameworks, dramatically reducing the time and cost needed to identify candidates for scalable carbon dioxide removal. Founded in 2023 by ex-Google researchers, Cusp AI collaborates with national laboratories and industrial partners to translate AI-generated molecules into pilot-scale demonstrations.
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