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Scientific Software Engineer; Polymer Simulations

Job in Greater London, London, Greater London, W1B, England, UK
Listing for: Cusp
Full Time position
Listed on 2026-05-20
Job specializations:
  • Research/Development
    Biomedical Science, Research Scientist
Salary/Wage Range or Industry Benchmark: 80000 - 100000 GBP Yearly GBP 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: Scientific Software Engineer (Polymer Simulations)
Location: Greater London

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

Due to expansion into a new area, we are seeking a Scientific Software Engineer (Polymer Simulations) to bridge the gap between our frontier AI models and real‑world industrial materials challenges.

You will build our atomistic polymer simulation capability from the ground up by designing the workflows, establishing the methodology, and setting the standard for how simulation integrates with our AI platform and experimental partners. This foundational work will directly underpin how CuspAI bridges the atomic scale and the macroscopic properties that determine whether a material succeeds or fails in the real world.

What

You Will Do

Method Development & Research

  • Design and implement atomistic simulation workflows for polymer systems from polymerisation and melt equilibration through to production runs.
  • Reach beyond MD and implement complementary simulation techniques to tackle complex industry problems.
  • Collaborate with our AI Research team to integrate machine learning models into atomistic simulation workflows, helping bridge the gap between learned representations, simulations, and experiments.

Experimental Validation & Partner Collaboration

  • Work closely with experimental partners to ensure simulation outputs are grounded in and validated against real lab measurements – trends must be reproducible, and results must be explainable.
  • Translate partner materials challenges into concrete simulation strategies, then execute and deliver findings with the clarity and rigour that industrial collaborations require.

Interdisciplinary Collaboration

  • Act as internal expert on polymer science, providing guidance to AI researchers on physical constraints and realistic material behaviours.
  • Work fluidly across a team of ML researchers, computational chemists, and experimentalists – contributing independently while building on a wide base of complementary expertise around you.
  • Contribute to CuspAI's core infrastructure and roadmap for multi‑scale materials discovery.
Must Have Skills and

Qualifications:
  • Extensive expertise in polymer simulation. You’ve worked across multiple projects and know from experience what breaks and why. You don’t just run simulations; you understand them.
  • Hands‑on experience with mapping simulations onto experiments, including proven ability to reproduce and explain real‑life trends.
  • The ability to build simulation workflows from scratch. We need someone who can design and implement methods, not just configure existing pipelines. When the right tool doesn’t exist, you write it.
  • Readiness to reach beyond your primary toolkit. Polymer simulations are intrinsically multi‑method, multi‑scale, and multi‑discipline, and we expect you to be able to pick up and implement approaches as the science demands.
  • Strong software engineering skills, with proficiency in Python, large‑scale projects, and hands‑on experience with simulation packages such as GROMACS or LAMMPS, and ASE or commercial equivalents.
  • The communication skills to work effectively across disciplines – AI researchers, computational chemists, and experimentalists will all be your collaborators.
Bonus Points (But Not Critical):
  • A PhD or equivalent in Materials Science, Physics, Chemistry, or Chemical Engineering,…
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