At a Glance
- Tasks: Develop graph neural networks for materials property prediction and integrate ML interatomic potentials.
- Company: Quantum Formatics, a leader in AI-accelerated materials discovery.
- Benefits: Competitive salary, mentorship opportunities, and a chance to shape the future of technology.
- Other info: Dynamic work environment with opportunities for growth and innovation.
- Why this job: Join a pioneering team and make a real impact in materials science with AI.
- Qualifications: Experience in computational science and a passion for mentoring.
The predicted salary is between 63000 - 77000 £ per year.
Quantum Formatics is seeking a Computational Scientist to advance an AI-accelerated materials discovery pipeline.
You will develop graph neural networks for materials property prediction and integrate ML interatomic potentials while benchmarking against experimental data.
You will collaborate with the Lead Scientist and experimental teams, mentoring future members as the team grows, and help shape the computational platform direction.
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AI Materials Scientist: Graph ML for Discovery + Equity in Cambridge employer: Quantum Formatics
Quantum Formatics is an exceptional employer, offering a dynamic work environment where innovation thrives. As an AI Materials Scientist, you will not only contribute to cutting-edge research but also enjoy opportunities for professional growth and mentorship within a collaborative team. Located in a vibrant area, the company fosters a culture of inclusivity and creativity, making it an ideal place for those seeking meaningful and rewarding employment.
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We think you need these skills to ace AI Materials Scientist: Graph ML for Discovery + Equity in Cambridge
Some tips for your application 🫡
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✨Brush Up on Your Statistics
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