Pod lead - Material Science (Terminal Bench Science)

Hello,

Greetings from ZettaMine!!!

Freelancing Opportunity :- We are hiring a Pod Lead – Material Science (Terminal Bench Science) for a short-term Frontier AI Research, Computational Materials Science & AI Model Evaluation project across the following locations:

Eligible Locations: 🇧🇩 Bangladesh | 🇧🇷 Brazil | 🇨🇴 Colombia | 🇪🇬 Egypt | 🇬🇭 Ghana | 🇮🇳 India | 🇮🇩 Indonesia | 🇳🇬 Nigeria | 🇹🇷 Turkey

Role: Pod Lead – Material Science (Terminal Bench Science)

Educational Eligibility: PhD, postdoctoral experience, or equivalent advanced technical experience in Materials Science, Metallurgy, or a closely related discipline.

Mode: Remote

Start: Immediate

Duration: 3 Weeks

Engagement Type: Short-Term Contract (Contractor Assignment)

Mandatory Eligibility Criteria

Technical Qualification:

• PhD, postdoctoral experience, or equivalent advanced technical expertise in Materials Science, Metallurgy, or a closely related field.
• 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 | Materials Characterization Data Analysis.
• Strong understanding of materials science fundamentals, numerical methods, computational modeling, and scientific validation.
• Experience reviewing complex technical work, scientific code, computational simulations, manuscripts, or research outputs.
• Ability to evaluate scientific assumptions, numerical accuracy, simulation convergence, and the reliability of computational results.
• Strong analytical skills to identify technical errors, unrealistic assumptions, edge cases, and flawed scientific methodologies.
• Experience mentoring technical teams, reviewing deliverables, or leading small research or engineering teams.
• Excellent written communication skills for providing precise technical feedback and documenting scientific requirements.

Preferred Technical Skills:

• Experience with computational materials science tools such as Quantum ESPRESSO, VASP, GPAW, ABINIT, LAMMPS, pymatgen, ASE, spglib, phonopy, pycalphad, MOOSE, FiPy, OVITO, or DREAM3D.
• Knowledge of machine-learned interatomic potentials, high-throughput materials simulations, or materials databases such as Materials Project.
• Familiarity with Docker, Git, CI/CD pipelines, automated testing, and high-performance computing (HPC) environments.
• Experience developing scientific benchmarks, simulation-based evaluations, programming challenges, or automated grading systems.
• Experience evaluating AI coding agents, terminal-based agents, or LLM-generated scientific solutions.

Availability:

• Minimum 40 hours per week.
• Availability to work at least 8 hours per day, with a minimum commitment of 4 hours per day.
• Minimum 4 hours of overlap with PST business hours.
• Immediate availability to start the short-term contract assignment.

What You’ll Work On:

• Lead and mentor a pod of approximately 5–10 technical trainers developing realistic, terminal-based materials science tasks for a frontier AI training and evaluation initiative.
• 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 authentic computational materials research workflows and require meaningful multi-step scientific reasoning rather than simple database lookups or library calls.
• Verify scientific accuracy across units, crystal symmetry, convergence criteria, electronic structure calculations, thermodynamic consistency, and simulation parameters.
• Validate computational environments, scientific software, pseudopotentials, interatomic potentials, and dependencies to ensure reproducible results.
• Review automated graders to ensure they accurately evaluate scientific outputs such as lattice parameters, formation energies, band gaps, elastic constants, phonon properties, phase fractions, diffusion coefficients, and microstructure metrics.
• Identify technical inaccuracies, unrealistic assumptions, incorrect numerical tolerances, and opportunities to bypass scientific calculations or simulations.
• Provide clear, actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval.
• Onboard trainers, allocate tasks, monitor quality and productivity, resolve technical blockers, and maintain consistent delivery standards.
• Maintain technical documentation, quality standards, and best practices throughout task development.

Important Offer Details

• Commitment: Minimum 40 hours per week.
• Working Hours: 8 hours per day.
• PST Overlap: Minimum 4 hours.
• Contract Duration: 3 weeks.

Interested Candidates: Please share your updated CV and LinkedIn profile at vyshnavi.e@zettamine.com.

Thanks & Regards,

Vyshnavi E

ZettaMine