The EPFL Data Science Lab (dlab) is looking for a motivated student assistant for the project “MegaBites: Measuring, Modeling and Improving the Sustainability of EPFL’s Food System”.
In a nutshell, the MegaBites project aims to improve the sustainability of EPFL’s food system using data science. Our ultimate goal is to reduce EPFL’s carbon footprint generated by the meals served on campus by 25–33% within two years.
Candidates must have a strong track record in data science and ideally an interest in food systems and their environmental impacts.
As the successful applicant, you will apply data science methods in order to quantify food consumption, at aggregated and individual levels. You will work with multiple databases consisting of ingredients, recipes, menus, nutritional values, carbon intensities, food waste, etc. You will elicit preferences in food consumption to analyze changes in individual behavior. You will explore fascinating questions at the intersection of data science, food consumption, and carbon footprinting, in an interdisciplinary team at the EPFL Data Science Lab.
You will be involved in the full research pipeline: data collection, data cleaning, data exploration, research design, data modeling, data visualization, and paper writing.
Experience with data processing, visualization, and machine learning is required. Knowledge of causal analyses, the design of observational studies or random control trials is a plus. The applicant should have performed well in classes such as Applied Data Analysis (CS-401) and Machine Learning (CS-433).
The position will start on 1 February 2024 and will last for 12 months. The student is expected to work on the project for 15 hours per week. The salary is CHF 24 per hour.
🤩 Looking forward to your applications! 🤩
How to apply
To apply, you should complete this short online form. The review of applications will begin immediately and will continue until the position is filled.