At a Glance
- Tasks: Lead AI research to revolutionise engineering with cutting-edge Physics models.
- Company: Pioneering startup backed by top-tier VCs, focused on AI for Physics.
- Benefits: Full ownership of projects, high impact work, and collaboration with elite teams.
- Other info: Dynamic environment with opportunities to publish influential research and mentor junior talent.
- Why this job: Shape the future of sustainable energy and efficient transport through innovative AI solutions.
- Qualifications: PhD/MSc in relevant fields and 5+ years in AI/ML research.
The predicted salary is between 80000 - 100000 £ per year.
BeyondMath is a pioneering startup, backed by top-tier VCs, on a mission to reshape the frontiers of engineering through Foundational AI models for Physics. We are replacing traditional, slow and expensive simulation methods with AI that rivals accuracy at orders of magnitude higher speed. We are moving beyond the "generic AI" hype to solve the world’s hardest physical engineering challenges in automotive, aerospace, and energy.
We are looking for a Senior AI Researcher who balances scientific curiosity with the engineering discipline required to see models thrive in production environments.
The Role
As a Senior AI Researcher, you will be a core architect of our technical roadmap. This is not a "siloed" research role; you will lead the transition from theoretical breakthroughs in Physics based Deep Learning to robust, scalable systems used by world-class engineers. You will have the creative freedom to set research agendas while ensuring our models remain grounded in physical reality and industrial-scale performance.
Key Responsibilities
- Architect Physics-AI Foundations: Lead the research and development of novel ML architectures (e.g., Transformers, GNNs, or Diffusion models) designed specifically to solve complex partial differential equations (PDEs) including aerodynamic simulations.
- Bridge Research & Production: Translate high-level mathematical concepts into clean, high-performance code. You won’t just "throw models over the wall"; you will ensure they are optimized for inference and integrated into our production design platform.
- Advance Geometry Representation: Pioneer new ways to represent complex geometric design variations for efficient use in deep learning models.
- Strategic Leadership: Mentor junior researchers and engineers. Help define our internal research standards, reproducibility pipelines, and high-performance compute (HPC) infrastructure requirements.
- External Impact: Represent BeyondMath in the global AI community. Publish influential research at top-tier conferences (NeurIPS, ICML, ICLR) and position the company as the leader in "AI for Physics."
- Cross-Functional Collaboration: Partner with CFD specialists and software engineers to ensure our models respect physical constraints while maintaining the speed advantages of neural networks.
About You
You are a rare hybrid: a scientist who loves the elegance of a theorem, but an engineer who gets a thrill from seeing a model successfully optimize a real-world turbine or airframe. You thrive in the ambiguity of a "greenfield" opportunity and have the grit to solve problems where no textbook solution exists.
Essential Requirements
- PhD or MSc in Computer Science, Physics, Mathematics, or a related quantitative field.
- 5+ years of post-grad experience in AI/ML research, with a demonstrable track record of models made it from the lab into production environments.
- Deep Technical Mastery: Expert-level proficiency in PyTorch, JAX, or TensorFlow, with a focus on building custom layers, loss functions, and optimization loops.
- Published Excellence: A strong record of high-quality publications in top-tier venues (e.g., NeurIPS, ICML, CVPR, or physics-specific AI journals).
- Systems Thinking: Experience with scalable training infrastructure, including distributed training across GPU clusters and data pipeline automation.
Highly Desirable
- Physics-ML Expertise: Experience with Physics-Informed Neural Networks (PINNs), Operator Learning (DeepONet/FNO), or Equivariant Neural Networks.
- Domain Knowledge: Familiarity with Aerodynamics, Fluid Dynamics, or Structural Mechanics.
- Engineering Rigor: Familiarity with C++, CUDA for low-level model optimization.
Why Join Us?
- Full Ownership: You will have a direct seat at the table in shaping the future of a company redefining an entire industry.
- High Impact: Your work will directly accelerate the transition to sustainable energy and more efficient transport.
- Elite Team: Work alongside veterans from world-leading AI labs and engineering firms in a culture of "impact with integrity."
AI Researcher in London employer: BeyondMath
BeyondMath is an exceptional employer for those looking to make a significant impact in the engineering sector. As a pioneering startup, we foster a dynamic work culture that encourages innovation and collaboration, providing ample opportunities for professional growth and development. Located at the forefront of AI technology, our team enjoys the unique advantage of working with leading global enterprises, ensuring that every employee contributes to groundbreaking advancements in physics and engineering.
StudySmarter Expert Advice🤫
We think this is how you could land AI Researcher in London
✨Join Aerospace Forums and Groups
Get involved in aerospace engineering forums and online communities, like the AIAA (American Institute of Aeronautics and Astronautics). It's a great way to meet industry peers and stay updated on job openings and trends in the field.
✨Attend Industry Conferences
Keep an eye on upcoming aerospace conferences and events where you can network with professionals and showcase your interest. Events like the Farnborough International Airshow are not just about flying machines; they're a goldmine for connections and potential job leads.
✨Spotlight Your Projects
Make sure to highlight any hands-on experience or projects on your portfolio that showcase your skills in aerospace engineering. Employers love seeing practical applications of theoretical knowledge. Show us what you've got!
✨Apply Directly on Company Websites
When you find companies you want to work for, head straight to their careers page to apply for full-time roles, like the one with BeyondMath for a AI Researcher. This often puts your application in front of the right people faster than just waiting for job boards!
We think you need these skills to ace AI Researcher in London
Some tips for your application 🫡
Show Off Your Technical Skills:When applying for the aerospace engineering role at BeyondMath, make sure to highlight your technical expertise. Include specific software skills, like CAD tools or simulation software, and any relevant engineering projects you’ve worked on. This is your chance to really shine and showcase your engineering toolkit!
Don't Skip Your Projects!:Include a section in your CV dedicated to projects that demonstrate your problem-solving abilities in aerospace engineering. Whether it's a university project, an internship, or personal work, we love seeing how you’ve applied your skills in real-world scenarios. Make it clear what your role was and the impact of the project.
Show Your Passion in Your Cover Letter:At BeyondMath, we're not just looking for skills – we want to know why you’re passionate about aerospace engineering. Use your cover letter to express what excites you about aviation technology and your career goals. Share any relevant experiences or inspirations that have led you to apply for this full-time position.
Tailor Your CV for Aerospace:Make sure your CV is specifically tailored to aerospace engineering. Focus on your education, any certifications, and your work experience, ensuring you highlight aspects that relate directly to the role. Don’t forget to mention any internships or apprenticeships that have given you hands-on experience.
How to prepare for a job interview at BeyondMath
✨Brush Up on Your Technical Knowledge
Aerospace engineering is all about technical precision, so make sure you’re comfortable with key concepts like aerodynamics, propulsion, and materials science. We recommend going through any relevant coursework or projects you’ve worked on – these real-world examples can illustrate your understanding during the interview with BeyondMath.
✨Showcase Your Projects with Confidence
Make sure to have a portfolio ready that details any significant projects you've worked on, whether it’s a group assignment or a personal endeavour. Be prepared to discuss the challenges you faced, the tools you used, like CAD software, and what you learned from the experience, as this will show your problem-solving skills in action.
✨Prepare for Technical Interviews
Expect some technical questions or even problem-solving exercises during your interview with BeyondMath. Get familiar with design challenges or theoretical problems related to aerospace; this can range from calculating lift and drag forces to materials selection under stress. Practising these can help you feel more at ease when faced with tricky questions.
✨Emphasise Your Passion and Teamwork Skills
As a full-time candidate, it’s crucial to convey your passion for aerospace engineering and your ability to work in teams. Highlight any group projects or internships you've done, focusing on how you collaborated with others to achieve a goal. Companies like BeyondMath love seeing candidates who not only have technical skills but also fit well within their team culture.
