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CuspAI

AI system designs candidate materials

Application Scientist

Biology & BiotechConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A PhD in chemistry, materials science, physics, chemical engineering, or a 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; or materials or cheminformatics with machine learning and optimisation.
  • A track record in one or more of the application areas: semiconductor processing, device-level modelling and electronics, photonic and thermal materials, catalysis, batteries, photovoltaics and multiscale kinetics, porous and soft materials, interfaces and separations, materials informatics, automated experimentation, or optimisation.
  • Python skills for data handling, analysis, automation, or modelling, and familiarity with version control using Git.
  • Ability to communicate with experimental and computational scientists and translate between them.
  • Industry experience, particularly in the semiconductor, electronics, energy, or chemical sectors.
  • Experience leading projects or collaborations with external partners, including writing technical scopes or proposals.
  • Experience with multiscale modelling, from atomistic to mesoscale, continuum, or device level.
  • Practical synthesis or processing experience, with an understanding of feasibility and reproducibility.
  • Professional software engineering practice, such as code review, testing, and deployment.
  • Prior experience in a start-up or fast-growth technology company.

Responsibilities

  • Own the scientific delivery of partner projects from scoping to results, working with technical programme managers, machine-learning researchers, platform engineers, and the lab integration team to ensure the platform answers partner questions and project learnings feed into company tools and workflows.
  • Help build cross-cutting capabilities for future projects, including validated workflows, harmonised data pipelines, and agentic design campaigns.
  • Lead partner projects from scoping to delivery as a key point of contact alongside technical programme managers.
  • Write technical scopes defining objectives, deliverables, success criteria, and timelines.
  • Prepare regular technical reports and presentations for partners and internal teams.
  • Apply and extend the platform to partner problems using simulation, machine learning, data-driven optimisation, or experiments as the project requires.
  • Design and steer discovery campaigns, including agentic and closed-loop campaigns with partner labs.
  • Assess when models, simulations, and data can be trusted, and contribute to validating them against experiments.
  • Translate platform recommendations into clear, executable experimental plans and communicate laboratory realities as requirements for internal teams.
  • Ensure data from partners and internal workflows are clean, structured, and consistent.
  • Work closely with partner labs, including through on-site visits at key project stages.
  • Build and automate workflows that run reliably at scale within the platform.
  • Relay partner feedback to technical programme managers, machine-learning researchers, and platform engineers to improve tools and workflows.
  • Stay informed about advances in the relevant field and contribute to the scientific direction of the team.

Desired Qualifications

  • Exceptional ability to communicate with experimental and computational scientists and translate between them.
  • Personal passion for CuspAI's mission and the potential of AI to unlock breakthroughs in materials science.

About the Company

CuspAI

AI system designs candidate materials

CuspAI builds an AI system for materials discovery that acts like a search engine for materials that do not yet exist. Its AI Materials Foundry uses a global network of labs, computing resources, and partners to design candidate materials when customers specify desired properties, spanning semiconductors, energy, climate, water treatment, and carbon capture. Unlike others, it combines AI-driven materials design with a broad, real-world Foundry network and high-profile advisers to turn requests into tangible material candidates. The company’s goal is to accelerate the creation of new materials by providing a scalable, end-to-end workflow that goes from property targets to candidate materials ready for testing and development, with ongoing expansion across the US, APAC, and Europe.

Company size
51-200
Company stage
Series B
Total funding
$580M
Headquarters
Cambridge, United Kingdom
Founded
2024

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