AI Research Scientist/ Research Engineer: Materials Discovery
Logical Intelligence · CA, US
2 days agoImpress employers and recruiters.
Choose from hundreds of resume examples.
Impress employers and recruiters.
Choose from hundreds of resume examples.
Tailor your resume to this AI Research Scientist/ Research Engineer: Materials Discovery role.
Rezi rewrites your resume against Logical Intelligence's job description. Free.
Tailor your resume to this AI Research Scientist/ Research Engineer: Materials Discovery role.
Rezi rewrites your resume against Logical Intelligence's job description. Free.
Don't guess if your resume is good enough.
See how it scores against the AI Research Scientist/ Research Engineer: Materials Discovery posting at Logical Intelligence — free, in seconds.
Don't guess if your resume is good enough.
See how it scores against the AI Research Scientist/ Research Engineer: Materials Discovery posting at Logical Intelligence — free, in seconds.
About the Role
As a Research Scientist on our material discovery team, you will help turn that idea into new molecules. You will build the AI systems that propose and evaluate candidates, and work with our partner labs so that every synthesis and measurement teaches the models something. You will join a highly interdisciplinary team of chemists, physicists, and machine learning scientists and engineers, where the biggest impact comes from working together.
Responsibilities
- Build and improve the AI systems behind our discovery loop, from candidate generation and screening to selecting which molecules to test next.
- Develop energy-based models that combine learned representations with physical and chemical knowledge to search chemical space more efficiently.
- Own model evaluation, including benchmarks on held-out chemical families, accuracy against both quantum-chemistry calculations and experiment, calibration of uncertainty estimates, prospective tests where the model predicts before the lab measures, and tracking across model versions.
- Compare AI predictions with measurements, investigate disagreements, and turn what you learn into concrete model changes, in collaboration with AI researchers and engineers.
- Design experiments with our partner labs so that each round of synthesis and testing is as informative as possible.
Requirements
- A background in machine learning, computational chemistry, physics, or a related field.
- Hands-on experience building ML models for real scientific problems.
- Experience designing evaluations and experiments that correlate with downstream performance.
- Excellent scientific writing and communication.
- Comfort working in an interdisciplinary team.
Skills
- Energy-based models
- Diffusion models
- Score-based models
- Generative approaches
- Chemistry knowledge
- Molecular ML
- Property prediction
- Generative molecular design
- ML interatomic potentials
- Quantum-chemistry workflows (e.g. DFT)
- Closed-loop design using real lab feedback
Experience Level
- PhD, or a Master’s plus relevant industry experience
Education Level
- PhD
- Master's
About the Company
- At Logical Intelligence, our mission is to accelerate the discovery of materials that make the next generation of technology possible, from light emitters and semiconductors to batteries, electric vehicles, and the chips behind AI and robotics.
- Discovering new materials requires an understanding of chemistry and physics to guide the search, and energy-based models let us build that understanding directly into our discovery loop.
- We work closely with industry and lab partners to shorten the path from research to real products.
- logicalintelligence.com