Scientific Software Engineer (Polymer Simulations) in London

Scientific Software Engineer (Polymer Simulations) in London

London Full-Time 60000 - 80000 € / year (est.) Home office (partial)
CUSP

At a Glance

  • Tasks: Design and implement cutting-edge polymer simulation workflows to solve real-world materials challenges.
  • Company: Join CuspAI, a pioneering AI company transforming materials science for a sustainable future.
  • Benefits: Competitive salary, equity options, generous holiday, and professional development budget.
  • Other info: Work in a dynamic environment with opportunities for growth and interdisciplinary collaboration.
  • Why this job: Make a tangible impact on sustainability and innovation in materials science with a diverse team.
  • Qualifications: Expertise in polymer simulations, strong software skills, and collaborative mindset required.

The predicted salary is between 60000 - 80000 € per year.

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, with a focus on multi‑scale or polymer modelling.
  • Prior experience in AI4Science such as generative molecular models, machine learning force fields, or property predictions.
  • Familiarity with first‑principles simulation methods.
  • Experience with HPC environments or cloud‑based simulation at scale.
  • Prior experience in a startup or client‑facing technical role.

Additional Considerations

This role could be based in our Cambridge, London, Amsterdam or Berlin offices, with the expectation of being in the office three days per week. Additionally, there may be regular travel required to other locations for collaboration and project work.

What We Offer

  • A competitive salary: We value and reward impact and growth.
  • Equity in CuspAI: You have a stake in the success of the company.
  • Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays.
  • ‘Gold Standard’ parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay – we look after you and your family while we work on the most important materials discovery problems together.
  • Professional development budget: We invest in your career development so you can stay up to date with the latest industry knowledge or add to your skills to increase impact and growth.
  • Solve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate‑related problems through the creation and application of bleeding‑edge SOTA technology and revolutionary techniques.
  • True interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science – work with world‑class researchers and engineers who enjoy sharing knowledge and supporting each other.

Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world.

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. Please let us know if you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.

Scientific Software Engineer (Polymer Simulations) in London employer: CUSP

CuspAI is an exceptional employer, offering a dynamic and collaborative work culture that thrives at the intersection of AI and materials science. With a strong focus on employee growth, we provide competitive salaries, equity options, and generous parental leave, alongside a professional development budget to enhance your skills. Join us in our Cambridge, London, Amsterdam, or Berlin offices, where your contributions will directly impact groundbreaking solutions for sustainability and innovation in materials discovery.

CUSP

Contact Detail:

CUSP Recruiting Team

StudySmarter Expert Advice🤫

We think this is how you could land Scientific Software Engineer (Polymer Simulations) in London

Tip Number 1

Network like a pro! Reach out to people in the industry, attend relevant meetups or conferences, and connect with CuspAI employees on LinkedIn. Building relationships can open doors that a CV just can't.

Tip Number 2

Show off your skills! If you’ve got a portfolio of projects or simulations you've worked on, make sure to share them during interviews. Demonstrating your hands-on experience can really set you apart from the crowd.

Tip Number 3

Prepare for technical interviews by brushing up on your polymer simulation knowledge and software engineering skills. Practice explaining complex concepts clearly, as communication is key when collaborating with interdisciplinary teams.

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the CuspAI team.

We think you need these skills to ace Scientific Software Engineer (Polymer Simulations) in London

Polymer Simulation
Method Development
Simulation Workflow Design
Machine Learning Integration
Experimental Validation
Interdisciplinary Collaboration
Software Engineering

Some tips for your application 🫡

Show Your Passion for Polymer Simulations:When writing your application, let us see your enthusiasm for polymer simulations! Share specific projects or experiences that highlight your expertise and how they relate to the role. We want to know what drives you in this field!

Be Clear and Concise:Keep your application straightforward and to the point. Use clear language to describe your skills and experiences, especially when discussing complex topics like simulation workflows. We appreciate clarity as it reflects your communication skills!

Tailor Your Application:Make sure to customise your application for the Scientific Software Engineer role. Highlight relevant experiences that align with our mission at CuspAI and how you can contribute to bridging AI and materials science. Show us why you're the perfect fit!

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the process smoother for everyone involved!

How to prepare for a job interview at CUSP

Know Your Polymer Simulations

Make sure you brush up on your polymer simulation knowledge before the interview. Be ready to discuss specific projects you've worked on, the challenges you faced, and how you overcame them. This will show that you not only understand the theory but also have practical experience.

Bridge Theory with Practice

CuspAI values the connection between simulations and real-world applications. Prepare examples of how you've successfully mapped simulations onto experiments in the past. Highlight any trends you've reproduced and explain how your findings contributed to the project.

Show Off Your Software Skills

Since strong software engineering skills are a must, be prepared to talk about your proficiency in Python and any simulation packages you've used, like GROMACS or LAMMPS. If you’ve built workflows from scratch, share those experiences to demonstrate your capability.

Communicate Across Disciplines

Collaboration is key at CuspAI, so practice articulating complex ideas clearly. Think of examples where you've worked with AI researchers, computational chemists, or experimentalists. Show that you can communicate effectively across different fields and contribute to interdisciplinary teamwork.