Pod Lead — Material Sciences (Terminal Bench Science) at Turing

About this opportunity

Turing is one of the world’s fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems.

What you would work on

• Lead and mentor a pod of technical trainers, ensuring consistent quality, productivity, and timely delivery of materials science tasks.
• Review scientific tasks end to end, including problem statements, crystal structures, interatomic potentials, thermodynamic databases, simulation inputs, reference solutions, and automated tests.
• Validate tasks involving density functional theory (DFT), molecular dynamics, computational thermodynamics, phase diagrams, crystallography, materials characterization, mechanical properties, semiconductors, and energy materials .
• Ensure tasks reflect realistic materials research workflows and require meaningful multi-step scientific reasoning rather than simple database lookups or library calls.

Check your fit

• Ph.D., postdoctoral experience, or equivalent advanced technical experience in Materials Science, Metallurgy, or a closely related discipline.
• Strong programming skills in Python, C/C++, Fortran, or Julia , with proficiency in Linux and terminal-based environments.
• Hands-on expertise in at least one major area: atomistic simulation, computational thermodynamics, mesoscale modeling, electronic structure calculations, or materials characterization data analysis .
• Strong understanding of materials science fundamentals, numerical methods, computational modeling, and scientific validation.

Prepare your application

• Tailor your CV to the relevant work and skills highlighted above.
• Prepare a brief example showing your relevant experience and the result you achieved.
• Confirm country eligibility, working hours, pay terms and any assessments on the application page.

Application

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