Hello,
Greetings from ZettaMine!!!
We are hiring Scientific Computing / Research Engineering Experts – Earth Sciences for a short-term AI Research & Scientific Computing project across: ?? India
Role: Scientific Computing / Research Engineering Expert – Earth Sciences
Experience: Ph.D., Postdoctoral Experience, or Equivalent Advanced Technical Experience
Mode: Remote
Engagement: Contractor / Short-Term Contract
Start: Immediate
Mandatory Eligibility Criteria
Technical Qualification:
- Strong programming skills in Python, R, Julia, Bash, or another relevant scientific programming language.
- Experience working in Linux or terminal-based environments.
- Strong expertise in at least one Earth Sciences domain, including Climate Science, Atmospheric Science, Geophysics, Oceanography, Geology, Hydrology, Environmental Modeling, Remote Sensing, Earth-System Science, or Geospatial & Environmental Data Science.
- Strong knowledge of numerical methods, scientific modeling, geospatial analysis, environmental data processing, time-series analysis, or quantitative data analysis.
- Ability to independently implement, test, debug, and validate computational Earth-science workflows.
- Strong understanding of coordinate systems, units, timestamps, missing-data handling, numerical precision, uncertainty, boundary conditions, spatial/temporal accuracy, and scientific reproducibility.
- Experience working with geospatial, climate, atmospheric, geological, hydrological, oceanographic, satellite, seismic, or environmental datasets.
- Ability to develop and validate computational workflows involving geospatial analysis, time-series processing, numerical modeling, interpolation, forecasting, remote sensing, or environmental risk analysis.
- Ability to debug issues involving geospatial projections, large datasets, dependencies, numerical stability, performance, scientific libraries, and file formats.
- Ability to develop rigorous scientific tasks with clearly defined inputs, expected outputs, numerical tolerances, and evaluation criteria.
- Ability to validate scientific outputs for numerical accuracy, physical consistency, spatial/temporal accuracy, and reproducibility.
Educational Qualification:
Mandatory: Ph.D., postdoctoral experience,
or equivalent advanced technical experience in Earth Sciences, Environmental Science, Geophysics, Atmospheric Science, Oceanography, Geology, Hydrology, Climate Science, Remote Sensing, or another closely related scientific discipline.
Preferred: Advanced research or professional experience in Climate Science, Atmospheric Science, Geophysics, Oceanography, Geology, Hydrology, Environmental Modeling, Remote Sensing, Earth-System Science, Geospatial Science, Scientific Computing, or related fields.
Availability:
- Full-Time – 40 Hours per Week.
- Minimum 4 hours of PST overlap per day.
- Ability to work remotely on a short-term scientific computing project.
- Immediate availability preferred.
- Ability to collaborate with project reviewers and incorporate feedback.
- Availability according to project requirements and deadlines.
Others:
- Personal laptop/desktop and stable high-speed internet.
- Strong written and verbal communication skills.
- Experience working with scientific computing and terminal-based environments.
- Experience with scientific/geospatial tools such as NumPy, pandas, SciPy, xarray, rasterio, GeoPandas, Cartopy, GDAL, or similar technologies.
- Experience with scientific data formats such as NetCDF, HDF5, GeoTIFF, Shapefiles, or GRIB.
- Familiarity with Docker, Conda, Git, CI/CD, automated testing, or HPC environments.
- Ability to ensure computational tasks are reproducible and execute successfully without runtime downloads.
- Robust attention to scientific accuracy, documentation, data provenance, and reproducibility.
- Research software engineering, scientific benchmarking, or automated grader development experience is an advantage.
- Experience evaluating AI coding/terminal agents or developing tasks and evaluations for AI systems is preferred.
- Publications or open-source contributions in Earth, environmental, geospatial, or computational sciences are advantageous.
- Ability to provide an updated Google Scholar profile/link where applicable.
What You’ll Work On:
- Design authentic, multi-step Earth Sciences tasks based on realistic research and computational workflows.
- Translate authentic Earth-science workflows into self-contained terminal benchmark environments.
- Prepare geospatial, climate, atmospheric, geological, hydrological, oceanographic, satellite, seismic, or environmental datasets.
- Build reproducible computational environments using appropriate scientific libraries and command-line tools.
- Implement expert solutions using Python, R, Bash, Julia, or other relevant scientific/domain-specific tools.
- Create tasks involving geospatial analysis, time-series processing, numerical modeling, interpolation, forecasting, remote sensing, environmental modeling, and environmental risk analysis.
- Develop automated tests for numerical accuracy, spatial/temporal accuracy, scientific consistency, numerical tolerances, metadata, file formats, and reproducibility.
- Define appropriate coordinate systems, units, timestamps, numerical tolerances, boundary conditions, missing-data handling, and expected scientific behavior.
- Validate that tasks are reproducible and execute successfully without runtime downloads.
- Debug issues involving geospatial projections, large datasets, dependencies, numerical precision, solver stability, performance, and file formats.
- Document input data provenance, scientific assumptions, computational requirements, expected outputs, edge cases, and known limitations.
- Develop benchmark tasks that evaluate whether AI agents can inspect scientific datasets, process geospatial and time-series data, reason through Earth-science problems, implement reliable computational models, operate command-line tools, troubleshoot scientific pipelines, and produce accurate, reproducible, and objectively verifiable scientific outputs.
Interested candidates kindly share your updated CV and Google Scholar profile/link to
[email protected]
Thanks & Regards,
Praneeth.N
ZettaMine
📌 [MQ] Scientific Computing / Research Engineering Experts – Earth Sciences (India)
🏢 ZettaMine Labs
📍 India