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CuspAI is an AI-driven materials discovery company using machine learning and computational chemistry to accelerate the discovery of breakthrough materials for energy, electronics, environment, and sustainability challenges. The company operates at the intersection of AI research, computational chemistry, and experimental science.
As an Application Scientist, you will own the scientific delivery of partner projects from scoping through results. You will work in a matrix structure with a home team while contributing across projects as expertise and demand evolve. Your role bridges experimental, computational, and machine learning teams to translate partner problems into actionable scientific plans.
Key responsibilities include:
- Leading partner projects end-to-end as a key technical contact alongside programme managers, writing technical scopes that define objectives, deliverables, success criteria, and timelines.
- Designing and steering discovery campaigns using simulation, machine learning, data-driven optimisation, or experiments as appropriate, including agentic and closed-loop campaigns with partner labs.
- Translating platform recommendations into executable experimental plans and translating lab findings back into requirements for internal teams.
- Ensuring data from partners and internal workflows are clean, structured, and consistent.
- Building and automating workflows that scale reliably within the platform.
- Relaying partner feedback to technical programme managers, ML researchers, and platform engineers to improve tools and workflows.
- Preparing regular technical reports and presentations for partners and internal stakeholders.
- Contributing to validated workflows, harmonised data pipelines, and agentic design campaigns that future projects depend on.
You will work across application areas including electronics (semiconductor processing, device modelling, photonic and thermal materials), energy (catalysis, batteries, photovoltaics, multiscale kinetics), environment (porous and soft materials, interfaces, separations), and cross-cutting areas (materials informatics, automated experimentation, optimisation).
The role is based in London with an expectation of being in the office at least three days per week. Regular travel to partner sites and other CuspAI offices (Cambridge, Amsterdam, Berlin) is expected for collaboration and project work.
REQUIREMENTS:
- PhD in chemistry, materials science, physics, chemical engineering, or related field, or equivalent industry experience.
- Deep, hands-on expertise in at least one of: atomistic simulation (including machine-learned force fields); experimental materials or chemistry (ideally with automation or high-throughput methods); materials or cheminformatics with machine learning and optimisation.
- Track record in one or more application areas (electronics, energy, environment, or cross-cutting materials informatics).
- Python skills for data handling, analysis, automation, or modelling; familiarity with version control (Git).
- Exceptional ability to communicate with both experimental and computational scientists and translate between them.
- Personal passion for AI-driven materials discovery and CuspAI's mission.
BONUS QUALIFICATIONS:
- Industry experience in semiconductor, electronics, energy, or chemical sectors.
- Experience leading projects or collaborations with external partners, including writing technical scopes or proposals.
- Experience with multiscale modelling (atomistic to mesoscale, continuum, or device level).
- Practical synthesis or processing experience with understanding of feasibility and reproducibility.
- Professional software engineering practice (code review, testing, deployment).
- Prior experience in a start-up or fast-growth technology company.
