Research Assistant - Water Demand Prediction

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 forecasting water demand using time series models or machine learning techniques to help manage water resources efficiently under varying climate conditions. It’s ideal for those interested in environmental data science, resource management, and climate adaptation.

Duties and Responsibilities

• Develop and apply time series models or machine learning techniques to forecast water demand.
• Analyse how climate variability affects water demand and supply.
• Collect and process data on water consumption, weather patterns, and resource availability.
• Use R, Python, or similar tools to build predictive models for water resource management.
• Prepare reports and visualisations of forecasting results for water management strategies.
• Collaborate on projects focused on sustainable water resource management.

Requirements

• Bachelor's, master's student, or recent graduate in a relevant field (Data Science, Environmental Science, Hydrology, Engineering).
• Interest in water demand forecasting, climate change, and resource management.
• Experience or willingness to learn time series analysis or machine learning techniques.
• Proficiency in 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 time series forecasting and machine learning for water demand prediction.
• In-depth understanding of water resource management under varying climate conditions.
• Proficiency in using R or Python for building and refining predictive models.
• Enhanced teamwork and communication skills in a research environment.
• Critical thinking for interpreting and presenting data-driven solutions for water management.

Benefits

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

Remote

• Flexible schedule, virtual work environment