Research Assistant - Carbon Emission Forecasting

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 statistical models or AI techniques to forecast carbon emissions under various policy scenarios and assess mitigation strategies for climate action. It’s ideal for individuals interested in climate change modelling, AI, and policy evaluation.

Duties and Responsibilities

• Develop and apply statistical models or AI techniques to forecast carbon emissions.
• Analyse carbon emission trends under different policy scenarios.
• Assess the effectiveness of various mitigation strategies using forecasting models.
• Collect and process relevant environmental and policy data for model development.
• Prepare reports and presentations on the outcomes of carbon forecasting and mitigation assessments.
• Collaborate on projects related to climate action and policy modelling.

Requirements

• Bachelor's, master's student, or recent graduate in a relevant field (Data Science, Environmental Science, Climate Studies, Computer Science).
• Interest in carbon emissions forecasting, AI, and climate policy analysis.
• Experience or willingness to learn statistical or AI-based modelling techniques (e.g., ARIMA, machine learning).
• Proficiency with programming languages (e.g., Python, R) and data analysis tools.
• Strong analytical, communication, and organisational skills.

Skills and Knowledge You Gain

• Hands-on experience with carbon emission forecasting models using AI or statistical methods.
• Practical understanding of the impact of policy scenarios on carbon emissions.
• Proficiency in data analysis and model development using R or Python.
• Enhanced teamwork and communication skills in a research setting.
• Critical thinking for interpreting and presenting climate action models and forecasts.

Benefits

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

Remote

• Flexible schedule, virtual work environment