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About the Role
We are seeking individuals with diverse backgrounds to join our team as Application Scientists. Successful candidates will possess the ability to translate partner problems into actionable plans, execute them, and communicate effectively across computational, experimental, and machine learning disciplines. This role operates within a matrix structure, allowing for contributions to various projects based on evolving needs and expertise.
Responsibilities
- Own the scientific delivery of partner projects from scoping to results.
- Ensure the platform addresses partner needs and that project learnings feed back into company-wide tools and workflows.
- Contribute to building cross-cutting capabilities such as validated workflows, harmonized data pipelines, and agentic design campaigns.
- Lead partner projects from scoping to delivery, serving as a key point of contact alongside technical program 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 optimization, or experiments.
- Design and steer discovery campaigns, including agentic and closed-loop campaigns with partner labs.
- Assess the trustworthiness of models, simulations, and data, and contribute to their validation against experiments.
- Translate platform recommendations into clear, executable experimental plans.
- Translate lab realities back into requirements for internal teams.
- Ensure data from partners and internal workflows are clean, structured, and consistent.
- Work closely with partner labs, including on-site visits at key project stages.
- Build and automate workflows that run reliably at scale within the platform.
- Relay partner feedback to TPMs, ML researchers, and platform engineers to improve tools and workflows.
- Stay informed about advances in the field and contribute to the scientific direction of the team.
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; materials or cheminformatics with machine learning and optimisation.
- A track record in one or more of the application areas: Electronics (Semiconductor processing, thin-film deposition, device-level modelling, molecular and polymer materials, photonic and thermal materials), Energy (Heterogeneous and electrocatalysis, ML-accelerated reaction kinetics, multiscale modelling, battery materials, photovoltaics), Environment (Solvation and interfacial simulation, porous and soft materials, formulations and soft matter, processes such as water treatment), or Cross-cutting (Materials and cheminformatics, high-throughput and automated experimentation, Bayesian, multi-objective and agentic optimisation).
- 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 to translate between them.
- A personal passion for CuspAI's mission and the potential of AI to unlock breakthroughs in materials science.
Skills
- Atomistic simulation
- Machine-learned force fields
- Experimental materials science
- Experimental chemistry
- Automation
- High-throughput methods
- Materials informatics
- Cheminformatics
- Machine learning
- Optimization
- Python
- Data handling
- Data analysis
- Automation
- Modelling
- Git
- Communication
- Translation between experimental and computational teams
Location
- London, UK
- Cambridge, UK
- Amsterdam, NL
- Berlin, DE
Work Type
- Hybrid (at least three days per week in office)
- Travel to partner sites and other CuspAI offices
Experience Level
- PhD or equivalent industry experience
- Industry experience (bonus)
- Experience leading projects or collaborations (bonus)
- Experience with multiscale modelling (bonus)
- Practical synthesis or processing experience (bonus)
- Professional software engineering practice (bonus)
- Prior experience in a start-up or fast-growth technology company (bonus)
Education Level
- PhD in chemistry, materials science, physics, chemical engineering, or a related field, or equivalent industry experience.
Salary/Compensations
- Competitive salary
Benefits
- Equity in CuspAI
- 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays
- 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) parental leave at full pay
- Professional development budget
About the Company
- CuspAI is a frontier AI company focused on accelerating the discovery of breakthrough materials essential for human progress.
- We leverage AI to unlock materials breakthroughs in months, aiming to solve challenges in energy, clean water, compute, and carbon capture.
- Our founding team comprises world-class researchers in AI, chemistry, and engineering.
- We are building a diverse, innovative team at the intersection of AI and materials science, fostering impactful partnerships to drive innovation, scalability, and industry collaboration.
- We are on the cusp of the on-demand materials era.
Equal Opportunity
- CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace.
- We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law.
- We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team.
- We will accommodate any specific adjustments required during or after the interview process.