ofi12.04.26
AI SCORE 8.5

Internship: Cocoa Farm Mapping with Remote Sensing & ML - Remote

$2K–$2K/month

About the Role

Join ofi as an intern focusing on Cocoa Farm Mapping with Remote Sensing and Machine Learning. This internship offers a unique opportunity to work remotely while contributing to sustainable cocoa farming practices.

What You'll Do

  • Preprocess and harmonize Sentinel-1, Sentinel-2, and ancillary data for model training.
  • Explore RAG architectures for geospatial classification, enhancing cocoa farm mapping.
  • Train and evaluate machine learning models using the ofi cocoa farm polygon database.
  • Benchmark RAG-enhanced models against traditional machine learning baselines.
  • Produce spatially explicit cocoa distribution maps for Côte d’Ivoire.
  • Document model performance, uncertainty, and generalization across regions.
  • Present results to forecast and sustainability teams at ofi.

Requirements

  • MSc student in Remote Sensing, Geomatics, Data Science, AI, Environmental Sciences, or related fields.
  • Strong interest in geospatial data, machine learning, and sustainability.
  • Experience with Python and geospatial workflows (e.g., Google Earth Engine, QGIS, GDAL, Rasterio).
  • Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
  • Curiosity about advanced ML concepts like representation learning, transformers, or RAG.
  • Ability to work independently and manage complex datasets and workflows.
  • Comfortable working with confidential information and willing to sign an NDA.

Nice to Have

  • Previous experience in agricultural data analysis.
  • Knowledge of sustainability practices in agriculture.
  • Familiarity with remote sensing technologies.

What We Offer

  • Hands-on experience with cutting-edge machine learning and RAG techniques.
  • Opportunity to work directly with one of the largest cocoa polygon datasets.
  • Contribution to real-world sustainability goals in the cocoa supply chain.
  • Competitive internship fee for the duration of your placement.
  • Flexible internship duration of four to six months, with the possibility to extend.
  • Collaborative environment in Amsterdam or Koog aan de Zaan.
  • Equal opportunity employer valuing diversity.
Why This Job8.5 of 10

This internship offers a unique opportunity to work with cutting-edge technologies in the cocoa supply chain, focusing on sustainability and machine learning.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

Proficient in Python, with hands-on experience in libraries such as TensorFlow and scikit-learn for implementing machine learning models specifically in geospatial contexts.

Self-motivated and disciplined to excel in a remote work environment, demonstrating effective time management skills and the ability to work independently while meeting project deadlines.

Familiarity with remote sensing data, particularly with Sentinel-1 and Sentinel-2 imagery, and the ability to preprocess and analyze geospatial datasets for machine learning applications in agriculture.

Learning Resources

Python for Data Science Handbookguide

Career Path

Intern: Cocoa Farm Mapping with Remote Sensing & ML(Now)Junior Data Scientist specializing in Geospatial Analysis(1-2 years)Data Scientist or Machine Learning Engineer with a focus on Remote Sensing(3-5 years)

Market Overview

Python Market Size 2024
$15.4B
Annual Growth
11.2%
AI Adoption in Python
72%
Investment in ML & Remote Sensing
+45%
Labour Demand for Python Developers
+22%
Avg Salary for Data Science Interns
$70K

Skills & Requirements

Required
PythonRemote SensingMachine Learning
Growing in Demand
TensorFlowGeospatial Data VisualizationCloud Computing (AWS/GCP)
Declining
MATLABArcGIS 9.x

Domain Trends

Increased Use of Remote Sensing for Agriculture
The agricultural sector is increasingly adopting remote sensing technologies, with a projected growth rate of 29% by 2025, highlighting the need for skilled professionals in this area.
Integration of Machine Learning in Geospatial Analysis
Machine Learning techniques are being integrated into geospatial analysis workflows, with 61% of organizations reporting improved accuracy in agricultural mapping and monitoring.
Rise of Cloud-Based Data Solutions
The shift to cloud-based solutions for data storage and analysis is accelerating, with a 35% increase in demand for cloud services in data science applications, providing opportunities for interns skilled in cloud technologies.

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