Research Assistant - Crop Yield Forecasting Using AI

Introduction

The Forecasting and Modelling Lab is offering an internship for bachelor's, master's students, or recent graduates to join as a Research Assistant. This role focuses on using machine learning models, such as Random Forest and LSTM, to predict crop yields based on weather, soil, and management data. It’s ideal for individuals interested in AI applications in agriculture and data-driven decision-making.

Duties and Responsibilities

• Develop and apply machine learning models (e.g. Random Forest, LSTM) to predict crop yields.
• Integrate weather, soil, and management data into predictive models.
• Analyse the performance of different AI models and refine them for better accuracy.
• Collect and process relevant datasets for training and validating the models.
• Prepare reports and presentations based on model results and insights.
• Collaborate on projects related to AI-driven forecasting in agriculture.

Requirements

• Bachelor's, master's student, or recent graduate in a relevant field (Data Science, Agricultural Science, Environmental Science, Computer Science).
• Interest in machine learning, crop forecasting, and data analysis.
• Experience or willingness to learn machine learning techniques and data modelling.
• Proficiency with programming languages (e.g., Python, R) and machine learning libraries.
• Strong analytical, communication, and organisational skills.

Skills and Knowledge You Gain

• Hands-on experience with machine learning models for crop yield prediction.
• Practical knowledge of integrating environmental and agricultural data into AI models.
• Proficiency in data processing, model development, and AI tools.
• Enhanced teamwork and communication skills in a research environment.
• Critical thinking for interpreting and presenting AI-driven forecasts in agriculture.

Benefits

• Experience Certificate
• Academic Credits for students
• Career Guidance, Support to Study Abraod

Remote

• Flexible schedule, virtual work environment