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- Tasks: Develop cutting-edge AI models for real-world engineering challenges.
- Company: Seer is a pioneering company at the forefront of AI and scientific computing.
- Benefits: Enjoy remote work flexibility, a collaborative culture, and opportunities for growth.
- Why this job: Make a real impact in high-value projects while working with an elite team.
- Qualifications: PhD or MSc in relevant fields; strong ML and programming skills required.
- Other info: Join a fast-growing environment where research meets industry.
The predicted salary is between 28800 - 48000 ÂŁ per year.
Join to apply for the Applied Research Scientist role at Seer
Join to apply for the Applied Research Scientist role at Seer
Machine Learning Researcher – Physics-Informed AI (Remote / UK-based)
Are you passionate about pushing the boundaries of what\’s possible at the intersection of AI and the physical world ? We\’re looking for a Machine Learning Researcher to join a world-class team building breakthrough technologies that merge scientific computing , deep learning , and engineering design .
About The Role
As a Machine Learning Researcher, you’ll play a central role in developing physics-informed AI models that challenge the limitations of traditional simulation and design tools. You\’ll work on complex, real-world problems in domains like aerospace, automotive, energy, and advanced manufacturing , applying and advancing techniques in:
- Differentiable physics
- Graph neural networks
- Transformers
- Bayesian optimization
- Surrogate modeling
You’ll collaborate with an elite, multidisciplinary team of researchers and engineers to deliver solutions that not only match but outperform classical methods.
What You’ll Do
- Conduct cutting-edge research in ML, applied to physical systems and design optimization
- Develop scalable models that integrate domain knowledge and physics constraints
- Design, test, and deploy algorithms that can be applied to customer-specific use cases
- Contribute to the broader research community through papers, open-source contributions, or internal knowledge sharing
What We’re Looking For
- Strong foundation in machine learning, applied mathematics, or computational physics
- Deep experience with deep learning frameworks such as PyTorch or JAX
- Solid grasp of numerical methods, differentiable programming, or PDE solvers
- PhD or MSc in a relevant field (or equivalent practical experience)
- Bonus: Experience in CAD, FEA, CFD, or related engineering tools
Why Join?
- Impact: Work on high-value, high-impact real-world problems
- Culture: Collaborate with an ambitious, open-minded, and intellectually curious team
- Flexibility: Fully remote within the UK or hybrid options available
- Growth: Be part of a fast-growing environment where research meets industry
If you’re excited by the idea of building the future of AI-driven engineering design , we’d love to hear from you.
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Applied Research Scientist employer: Seer
Contact Detail:
Seer Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Research Scientist
✨Tip Number 1
Familiarise yourself with the latest advancements in physics-informed AI and machine learning. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of machine learning and applied research. Attend relevant conferences or webinars, and connect with researchers on platforms like LinkedIn to gain insights and potentially get referrals.
✨Tip Number 3
Showcase your practical experience with deep learning frameworks such as PyTorch or JAX. Consider working on personal projects or contributing to open-source initiatives that demonstrate your skills in these areas.
✨Tip Number 4
Prepare to discuss real-world applications of your research. Think about how your work can solve complex problems in industries like aerospace or energy, and be ready to share specific examples during your interview.
We think you need these skills to ace Applied Research Scientist
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Applied Research Scientist position. Familiarise yourself with the key areas such as machine learning, physics-informed AI, and the specific technologies mentioned in the job description.
Tailor Your CV: Customise your CV to highlight relevant experience and skills that align with the job description. Emphasise your background in machine learning, applied mathematics, or computational physics, and include any specific projects or research that demonstrate your expertise in these areas.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and its applications in physical systems. Discuss how your experience aligns with the company's goals and mention any specific projects or achievements that relate to the role.
Showcase Your Research Contributions: If you have published papers or contributed to open-source projects, be sure to mention these in your application. Highlighting your contributions to the research community can set you apart from other candidates and demonstrate your commitment to advancing the field.
How to prepare for a job interview at Seer
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning frameworks like PyTorch or JAX. Highlight specific projects where you've applied these tools, especially in relation to physics-informed AI or similar domains.
✨Demonstrate Problem-Solving Abilities
Expect to tackle complex, real-world problems during the interview. Practice explaining your thought process and how you would approach challenges in areas like aerospace or energy using advanced modelling techniques.
✨Engage with the Research Community
Discuss any contributions you've made to the research community, such as papers or open-source projects. This shows your commitment to advancing the field and your ability to collaborate with others.
✨Prepare for Collaborative Scenarios
Since the role involves working with a multidisciplinary team, be ready to share examples of successful collaborations. Emphasise your communication skills and how you adapt to different perspectives in a team setting.
