Pod Lead - Material Science (Terminal Bench Science) | $20 - $28/hr

Qualification: Ph.D, postdoctoral experience, or equivalent advanced technical experience in Materials Science, Metallurgy, or a closely related discipline.

Job Type: Short-term contract

Location: Remote

Domain: Materials Science | Computational Modeling | AI Training

Role Overview

We are seeking a Pod Lead for Material Science to guide a specialized team of technical trainers. In this role, you will leverage your deep expertise in computational materials science and your leadership skills to oversee workflows, validate complex scientific tasks, and ensure the delivery of high-quality, rigorous technical outputs.

Key Responsibilities

- Lead and mentor a pod of technical trainers, ensuring quality, productivity, and timely delivery.
- Review end-to-end scientific tasks, including problem statements, simulation inputs, and reference solutions.
- Validate complex materials science tasks (DFT, MD, thermodynamics, crystallography, semiconductors, etc.) to ensure scientific correctness and realism.
- Verify units, crystal symmetry, convergence criteria, and simulation parameters for accuracy.




- Review automated graders to ensure they evaluate meaningful scientific outputs (e.g., lattice parameters, band gaps, elastic constants).
- Identify technical inaccuracies, unrealistic assumptions, and bypass opportunities in scientific calculations.
- Onboard trainers, allocate work, monitor throughput, escalate blockers, and maintain technical documentation.

Key Requirements

- Previous experience leading a team.
- Ph.D., postdoctoral experience, or equivalent advanced technical experience in Materials Science, Metallurgy, or a closely related discipline.
- Robust 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.

Role Details

- Start Date: Immediate
- Availability: 8 hours per day with an overlap of 4 hours with PST.
- Vetting Process: Interest Check Form (ICF), AI Interview, Delivery Review.

📌 Pod Lead - Material Science (Terminal Bench Science) (India)
🏢 Codefeast
📍 India