Research Assistant - Energy 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 time series forecasting methods in R or Python to predict energy demand and optimise the integration of renewable energy sources like solar and wind. It’s ideal for those interested in renewable energy, data science, and optimisation.

Duties and Responsibilities

• Develop and apply time series forecasting models to predict energy demand.
• Optimise the integration of renewable energy sources (e.g., solar, wind) into the energy grid.
• Analyse and interpret energy demand and supply patterns using R or Python.
• Collect and process energy data to build accurate forecasting models.
• Prepare reports and visualisations of forecasting results and optimisation strategies.
• Collaborate on projects related to renewable energy integration and forecasting.

Requirements

• Bachelor's, master's student, or recent graduate in a relevant field (Data Science, Energy Engineering, Environmental Science, Computer Science).
• Interest in renewable energy forecasting, time series analysis, and optimisation.
• Experience or willingness to learn time series forecasting methods (e.g., ARIMA, Prophet).
• Proficiency with programming languages (R, Python) and data analysis tools.
• Strong analytical, communication, and organisational skills.

Skills and Knowledge You Gain

• Hands-on experience in time series forecasting for energy demand and supply.
• Practical knowledge of renewable energy integration into energy grids.
• Proficiency in using R or Python for forecasting and optimisation tasks.
• Enhanced teamwork and communication skills in a research environment.
• Critical thinking for interpreting and presenting energy forecasting models.

Benefits

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

Remote

• Flexible schedule, virtual work environment