What You Will Do & Learn Model Soil Carbon & GHGs: Learn to set up, calibrate, and validate process-based models (such as DayCent, DNDC, or DSSAT) to estimate soil carbon sequestration and emission reductions across agricultural landscapes.

Master Carbon Standards: Gain hands-on experience with leading carbon registries and methodologies (e.g., Verra VM0042 and VMD0053), covering structural validation, uncertainty quantification, and Model Validation Report (MVR) development.

Build Scalable Pipelines: Write reproducible, production-grade Python code and geospatial workflows to scale our models across regions.

Collaborate & Defend Scientific Models: Help prepare rigorous technical documentation, data visualizations, and scientific rebuttals for third-party auditors (VVBs) and carbon market evaluators.

What We Are Looking For Educational Background Bachelor’s or Master’s degree in Computer Science (B.Tech / M.Tech preferred), Applied Mathematics, Computational Biology,



or related fields.

Core Skills

Robust logical and analytical thinking, and effective technical communication.

Core Foundations

Production-grade Python, Git version control, statistical modeling, and geospatial data handling.

Coding Toolkit

Hands-on experience with Python libraries and geospatial tools (e.g., GeoPandas, Rasterio) or GIS tools. BONUS POINTS (NICE-TO-HAVES) Prior exposure to biogeochemical models (DayCent, DNDC, DSSAT) through coursework, research, or internships.

Familiarity with Bayesian statistics, machine learning surrogates, or remote sensing data (Sentinel-2, MODIS).

Interest in agricultural systems across India, Southeast Asia, or Sub-Saharan Africa.

Habit of using modern AI/LLM-assisted workflows to accelerate research, data processing, and code development.

📌 Intern — Junior Carbon & GHG Modeler (India)
🏢 Varaha
📍 India