Lead AI Materials Application Scientist

CuspAI; Cambridge; Hybrid; GBP 75,000 - 120,000; Full time

Benefits offered by this job

Equity stake

28 days holiday

Development budget

Parental leave

Job summary

CuspAI in London, Cambridge, Amsterdam, or Berlin is seeking researchers who can turn partner problems into actionable plans, delivering results that bridge experimental and computational work. You will lead projects, coordinate with ML researchers and platform engineers, and ensure data-driven campaigns are aligned with partner goals.

Ideal candidates bring a PhD in a relevant field, hands-on experience across simulations, experiments, or ML in materials, and a passion for advancing AI-powered

Qualifications

• PhD in chemistry, materials science, physics, chemical engineering, or a related field.
• Hands-on expertise in atomistic simulation, experimental materials/chemistry, or ML-driven materials informatics.
• Experience in one or more of the listed application areas.
• Python skills for data handling and automation; Git proficiency.
• Excellent ability to communicate across experimental and computational teams.

Responsibilities

• Lead partner projects from scoping to delivery, as a key contact alongside TPMs.
• Write technical scopes defining objectives, deliverables, success criteria, and timelines.
• Prepare regular technical reports and presentations for partners and internal teams.
• Apply platform to partner problems using simulation, ML, data-driven optimisation, or experiments.
• Design and steer discovery campaigns with partner labs.
• Translate platform recommendations into executable experimental plans.

Skills

Python

Communication

ML in materials

Education

PhD in chemistry / materials science

Tools

Git

Job description

CuspAI in London, Cambridge, Amsterdam, or Berlin is seeking researchers who can turn partner problems into actionable plans, delivering results that bridge experimental and computational work. You will lead projects, coordinate with ML researchers and platform engineers, and ensure data-driven campaigns are aligned with partner goals.

Ideal candidates bring a PhD in a relevant field, hands-on experience across simulations, experiments, or ML in materials, and a passion for advancing AI-powered