Application Scientist

The Role

We hire across a spectrum of backgrounds. Some Application Scientists are computational (atomistic and molecular simulation, machine-learned force fields), some are experimental (synthesis, processing, characterisation, lab automation), and some are data-driven (materials and cheminformatics, optimisation). What they share is the ability to turn a partner’s problem into a plan, deliver it, and translate fluently between experimental, computational, and machine learning teams.

We operate a matrix structure. You will have a home team, but may contribute to projects in another pillar as demand and your expertise evolve.

Your Impact

You will own the scientific delivery of partner projects, from scoping to results. Working with our technical programme managers, ML researchers, platform engineers, and lab integration team, you will make sure our platform answers the questions that matter to partners, and that what is learned on each project feeds back into tools and workflows used across the company.

Alongside delivery, you will help build the cross-cutting capabilities that future projects depend on, such as validated workflows, harmonised data pipelines and agentic design campaigns.

Application Areas

We are particularly interested in candidates with expertise in one or more of the areas below. You do not need to cover a whole pillar.

• Electronics: Semiconductor processing, device-level modelling and electronics, photonic and thermal materials

• Energy: Catalysis, batteries, photovoltaics and multiscale kinetics.

• Environment: Porous and soft materials, interfaces, and separations

• Cross-cutting: Materials informatics, automated experimentation and optimisation.

What You Will Do

Project leadership and delivery

• Lead partner projects from scoping to delivery, as a key point of contact alongside the technical program managers.

• Write technical scopes that define objectives, deliverables, success criteria, and timelines.

• Prepare regular technical reports and presentations for partners and internal teams.

Science and campaigns

• Apply and extend our 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.

Bridging experimental and computational teams

• Translate platform recommendations into clear, executable experimental plans, and translate lab realities back into requirements for internal teams.

• Make sure data from partners and our own workflows are clean, structured, and consistent.

• Work closely with partner labs, including on-site visits at key stages of a project.

Capability and product development

• Build and automate workflows that run reliably at scale within our platform.

• Relay partner feedback to TPMs, ML researchers, and platform engineers to improve tools and workflows.

• Stay informed about advances in your field and contribute to the scientific direction of your team.

Must Have Skills and Qualifications

• 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; materials or cheminformatics with machine learning and optimisation.

• A track record in one or more of the application areas above.

• Python skills for data handling, analysis, automation or modelling, and familiarity with version control (Git).

• Exceptional ability to communicate with both experimental and computational scientists, and to translate between them.

• A personal passion for CuspAI's mission and the potential of AI to unlock breakthroughs in materials science.

Bonus Points (But Not Critical)

• 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 what makes a route feasible and reproducible.

• Professional software engineering practice, such as code review, testing and deployment.

• Prior experience in a start-up or fast-growth technology company.

Additional Considerations

These roles can be based in our London, Cambridge, Amsterdam, or Berlin offices, with the expectation of being in the office at least three days per week. There may be regular travel to partner sites and other CuspAI offices for collaboration and project work.

What We Offer

• A competitive salary: We value and reward impact and growth