Research Scientist - Material Modelling in London

Research Scientist - Material Modelling in London

London Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
Physicsx

At a Glance

  • Tasks: Join a dynamic team to advance machine learning in materials science and tackle real-world challenges.
  • Company: PhysicsX, a deep-tech company revolutionising hardware innovation with AI-driven solutions.
  • Benefits: Enjoy equity options, generous leave, free lunches, and a supportive work environment.
  • Other info: Flexible hybrid work model and commitment to diversity and inclusion.
  • Why this job: Make a tangible impact in engineering while collaborating with top-tier professionals.
  • Qualifications: PhD in relevant fields and hands-on experience with machine learning in materials.

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

About us

PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.

What you will do

  • Work closely with a multi-disciplinary team ranging from computational chemists with varied domain expertise to machine learning engineers to employ and advance the state-of-the-art machine learning techniques for solving a variety of problems in materials.
  • Develop and apply machine learning interatomic potentials (MLIPs) to model atomistic systems, leveraging and extending state-of-the-art frameworks and benchmark datasets.
  • Design and run experiments on large-scale chemistry and materials datasets, iterating on model architectures to improve accuracy, transferability, and generalisation across systems.
  • Own research workstreams at different levels of scope, depending on seniority, from model development through to evaluation on real-world materials problems.
  • Collaborate with the broader research team to ensure your models are robust, reproducible, and translatable into production-ready pipelines.
  • Work on high-performance computing infrastructure to handle the scale and complexity of atomistic simulations and generative modelling tasks.
  • Communicate your work internally and externally — through paper publications, industry workshops, and customer conversations — tailoring the message for both academic and non-academic audiences.
  • Mentor colleagues with less experience in computational chemistry or materials ML as the team grows.

What you bring to the table

  • Enthusiasm for applying machine learning to real-world materials science and computational chemistry challenges, with a genuine interest in seeing your research have industry impact.
  • Ability to scope and effectively deliver research projects, balancing rigour with pragmatism.
  • Strong problem-solving skills and the ability to move quickly from a materials or chemistry challenge to a tractable computational formulation.
  • Excellent collaboration and communication skills — with research colleagues, engineers, and customers alike.
  • PhD in computational chemistry, physics, materials science or a closely related field.
  • Hands-on experience in using and fine-tuning at least one MLIP backend such as MACE or FAIRChem/OCP and their integration into larger computational framework.
  • Direct experience with established chemistry and materials benchmark datasets, such as OC20, OC22, or the Materials Project.
  • Proficiency in Python and experience working in high-performance computing environments as well as experience in contributing towards a large multi-module codebase.
  • Experience with generative models preferably applied to molecular or materials systems.

What we offer

  • Build what actually matters: Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society.
  • Learn alongside exceptional people: Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better.
  • Influence over hierarchy: We operate with a flat structure: good ideas win - wherever they come from.
  • Sustainable pace, long-term ambition: Building meaningful technology is a marathon, not a sprint.
  • Equity options - share meaningfully in the company you’re helping to build.
  • 10% employer pension contribution - because investing in future matters.
  • Free office lunches - to keep you energised and focused.
  • Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.
  • YellowNest nursery scheme - to help working parents manage childcare costs.
  • 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.
  • Private medical insurance - 100% employee cover, giving you complete peace of mind.
  • Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing.
  • Eye tests - because good work depends on good health.
  • Personal development - dedicated support for learning, development, and leveling up over time.
  • Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it.
  • Bike2Work scheme and Season ticket loan - to make getting to work easier and greener.
  • Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric.

We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply.

We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.

Physicsx

Contact Details:

Physicsx Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Research Scientist - Material Modelling in London

Get Involved in Research Communities

Dive headfirst into the scientific research world by joining relevant communities and forums. Engage in discussions, share your insights, and even attend conferences or seminars in your field. This not only boosts your visibility but can also lead to potential job opportunities—don't forget to connect with like-minded folks!

Show Off Your Research Projects

Have you worked on any cool research projects? Make it easy for potential employers to see your work by creating a portfolio or a personal website. This way, when you apply for roles like the one at Physicsx, you can point them to your projects and publications, showcasing your expertise directly.

Utilise Professional Networks

Networking is key in scientific research. Join professional bodies or organisations related to your field. They often have job boards and resources tailored for job seekers. Make connections with professionals who may know about openings or can give you tips on landing a full-time position.

Keep Your Eyes on Openings & Apply Directly

Don’t just rely on job boards! Keep an eye on the careers section of the websites of companies like Physicsx. Apply directly through their website because sometimes they post jobs there before anywhere else. Plus, it shows your proactive approach!

We think you need these skills to ace Research Scientist - Material Modelling in London

Machine Learning
Computational Chemistry
Materials Science
Python
High-Performance Computing
Model Development
Data Analysis

Some tips for your application 🫡

Highlight Your Research Experience:When applying for a full-time role in scientific research, make sure to emphasise your research experience prominently in your CV. Share specific projects you’ve worked on, the methodologies you used, and any significant findings. If you’ve published papers or presented at conferences, definitely include that too – it shows you’re on it in the academic world!

Tailor Your Cover Letter to the Research Area:Your cover letter should reflect your passion for the specific area of research at Physicsx. Mention relevant experiences that align with the organisation’s goals or projects. This shows that you’ve done your homework and are genuinely interested in the position – plus, it helps us see how you’d fit into the team dynamics.

Showcase Your Data Analysis Skills:In scientific research, data analysis skills are a big deal! Make sure to detail any relevant analytical tools or software you’re familiar with, like R, Python, or statistical packages. Employers are keen to know you can handle the data-heavy elements of the role, so add specific examples where you’ve used these skills effectively.

Discuss Your Future Research Goals:In your motivation section, it’s a great idea to talk about your future research goals and how they align with the work being done at Physicsx. This shows that you’re not just looking for any job, but rather a chance to contribute meaningfully to the field. We love to see applicants who are forward-thinking and enthusiastic about their research journey!

How to prepare for a job interview at Physicsx

Showcase Your Research Skills

In scientific research, it’s crucial to demonstrate your ability to design and conduct experiments. Come armed with examples of past projects where you've developed hypotheses, collected data, and analysed results. Be ready to discuss any specific methodologies or tools you’ve used, like PCR techniques or statistical software.

Prepare for Technical Questions

Expect some technical questions specific to your field. Make sure you're up to speed with recent advancements in scientific research related to the role at Physicsx. Brush up on concepts relevant to their projects and be prepared to discuss how you would approach a specific research problem or challenge they might face.

Know Your Publications

If you've authored or co-authored any papers, be prepared to discuss them! Highlighting your contributions to published research can really set you apart. It shows not only your expertise but also your ability to communicate complex ideas clearly, which is key in scientific research roles.

Exhibit Your Team Spirit

In full-time roles, collaboration is often at the heart of scientific research. Prepare examples that show how you've successfully worked in teams, dealt with conflicts, or contributed to group projects. We want to know how you can work effectively with the team at Physicsx to drive research projects forward.