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Machine learningData engineeringA/B testingLeadership
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No sponsorship evidence yet
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Confirmed live todayWhen a source last listed this job as open.
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- Can’t check pay against the visa rules
- No salary stated. Singapore Employment Pass needs at least SGD 67,200 a year. Source: https://www.mom.gov.sg/passes-and-permits/employment-pass/eligibility, rules effective 2025-01-01.
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Sponsorship unknown
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About the role
ABOUT CUSPAI
CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering.
We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock.
We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters.
We’re on the cusp of the on-demand materials era. Join us.
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 a
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