At a Glance
- Tasks: Train and fine-tune machine-learning models for cutting-edge materials research.
- Company: Join a pioneering company at the forefront of machine learning and materials science.
- Benefits: Competitive salary, equity options, and comprehensive benefits package.
- Other info: Inclusive workplace committed to diversity and accessibility.
- Why this job: Make a real impact in innovative research while working with top scientists.
- Qualifications: PhD in relevant field and hands-on experience with ML models required.
The predicted salary is between 70000 - 90000 £ per year.
We are looking for a Machine Learning Engineer to take ownership of training and fine-tuning machine-learning interatomic potentials (MLIPs) for magnetic and structural materials. You will work at the intersection of modern ML and first‑principles simulation, leveraging our DFT datasets to feed our models and pushing MLIP architectures into new physical regimes; particularly spin‑dependent interactions.
What You’ll Do
- Pre‑train and fine‑tune MLIPs (MACE, CHGNet, Orb, or equivalent) for solid‑state systems, with a focus on magnetic materials.
- Design and build DFT training‑set workflows, including active learning loops, convergence testing, and data curation.
- Extend existing MLIP architectures to capture spin‑lattice interactions.
- Build and maintain automated, reproducible workflows for dataset generation and model iteration using tools such as AiiDA, FireWorks, or equivalent frameworks.
- Work directly with materials scientists to translate physical intuition about magnetism into training objectives and dataset design decisions.
Skills & Qualifications
- PhD in physics, chemistry, materials science, or a closely related field; solid‑state focus strongly preferred.
- Proven hands‑on experience training or fine‑tuning MLIPs, with a clear understanding of training dynamics, loss landscapes, and generalisation behaviour.
- Experience working with DFT‑generated training sets and experimental material science data; understanding what makes a dataset sufficient or deficient for a given system, and being able to work with our DFT team or our experimental scientists to diagnose and close gaps.
- Strong Python skills and production‑quality research code; experience with PyTorch or JAX; ideally also C/C++ or Rust.
- Familiarity with atomistic simulation packages (VASP, Quantum Espresso, LAMMPS, or similar).
- Evidence of significant research impact through publications in ML for atomistic modelling, computational materials science, or related technical disciplines.
Nice to Have
- Background in long‑range or equivariant message‑passing architectures for extended systems.
- Experience with spin‑polarised or non‑collinear DFT calculations.
- Contributions to open‑source atomistic simulation or ML packages.
- Experience with automated workflow frameworks such as AiiDA or Fireworks.
We offer competitive salary, generous equity and benefits.
EEO & Accessibility Statement
Diffractive is an equal opportunities employer. We are committed to creating an inclusive environment for all employees and welcome applications from people of all backgrounds, experiences, and identities. If you require any adjustments or accommodations at any point during the interview process, please let us know – we will be happy to help.
Research Scientist/Engineer, GNNs in London employer: Diffractive Labs
At Diffractive, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the field of machine learning and materials science. Our commitment to employee growth is evident through competitive salaries, generous equity options, and a supportive environment that encourages contributions from diverse backgrounds. Located at the forefront of research, we provide unique opportunities to work with cutting-edge technologies and make a significant impact in the scientific community.
StudySmarter Expert Advice🤫
We think this is how you could land Research Scientist/Engineer, GNNs in London
✨Get Involved in Research Communities
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✨Utilise Professional Networks
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We think you need these skills to ace Research Scientist/Engineer, GNNs in London
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 Diffractive Labs. 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 Diffractive Labs. 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 Diffractive Labs
✨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 Diffractive Labs. 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 Diffractive Labs to drive research projects forward.
