Periodic Labs
11 - 50 employees
Founded 2025
💼 Consulting
🏭 Manufacturing
🤖 Artificial Intelligence
🔥 Funding within the last year
💰 $300M Seed on 2025-10
Consulting • Manufacturing • Artificial Intelligence
Periodic Labs is a company building AI scientists and autonomous laboratories to accelerate discovery in the physical sciences. They combine advanced machine learning agents with automated experimental platforms to generate high-quality experimental data, automate materials design, and discover technologies like higher-temperature superconductors. The team includes researchers who helped build major AI systems (e. g. , ChatGPT, DeepMind and OpenAI projects) and the company partners with industry to deploy custom AI agents for scientific R&D.
Research Scientist, Condensed Matter Theory
Job not on LinkedIn
🕒 April 12
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Periodic Labs
11 - 50 employees
Founded 2025
💼 Consulting
🏭 Manufacturing
🤖 Artificial Intelligence
🔥 Funding within the last year
💰 $300M Seed on 2025-10
Consulting • Manufacturing • Artificial Intelligence
Periodic Labs is a company building AI scientists and autonomous laboratories to accelerate discovery in the physical sciences. They combine advanced machine learning agents with automated experimental platforms to generate high-quality experimental data, automate materials design, and discover technologies like higher-temperature superconductors. The team includes researchers who helped build major AI systems (e. g. , ChatGPT, DeepMind and OpenAI projects) and the company partners with industry to deploy custom AI agents for scientific R&D.
📋 Description
• Join a world-class team of scientists and engineers pushing the boundaries of physics research in a groundbreaking lab where AI, theory, and automation unlock discoveries at unprecedented speed and scale. • Work on using theoretical modeling to connect first-principles calculations and experiments. • Collaborate with computational and experimental scientists and ML researchers.
🎯 Requirements
• PhD in formal condensed matter theory for quantum materials. • Deep expertise in relating theoretical models to real materials and experiments. • Experience with running first principles calculations like density functional theory on realistic systems. • Experience with deep learning, including but not limited to graph neural networks. • Experience in modeling superconductivity and/or magnetism.
🏖️ Benefits
• Health insurance • Flexible work arrangements • Professional development opportunities
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