Internship As Statistical Inferences in Food Sector - Paris, France - Breega

Breega

Entreprise vérifiée

Paris, France

il y a 2 semaines

Posté par:

Sophie Dupont

beBee Recruiter

StageSHIP

Description

Carbon Maps is the first comprehensive climate management platform for the food industry.
Our food system is a major contributing factor to global greenhouse gas emissions, deforestation and water consumption worldwide.

At Carbon Maps, we are on a mission to help the food industry reduce its environmental footprint, by
collecting and analyzing data across all stages of the food chain, from farmers to consumers.

The Carbon Maps' cloud platform enables
agri-food industry players to:

perform
rapid, high-precision assessments of the environmental impact of their products, from raw materials to processing to distribution and agricultural raw materials;

- gain actionable insights and tools to help them execute and monitor their climate plans.

Carbon Maps relies on widely accepted
scientific models and environmental standards (GHG Protocol, ISO 14040 & 14044, IPCC).

The Life Cycle Assessment (LCA) method is widely used in the assessment of the environmental impacts of food products.

It requires a good knowledge of the supply chain of these products to quantify the emissions of the different stages of their life cycle.

However, the supply chains of food products are generally complex and their analysis often requires an intensive data collection phase.

The aim of this internship is to work on methods to statistically infer the supply chain of a food product based solely on Open Data. We are therefore looking for an intern who will work with the scientific team on this topic.

In particular:

Define the modelling choices and programs in Python
Test and calibrate the models on the basis of real data

THIS INTERNSHIP IS FOR YOU IF...

You are interested in food and agriculture
You are sensitive to environmental and climate issues
You are autonomous, curious and creative
You have a good knowledge of the most advanced statistical techniques (ML, NLP, Constraint Programming, etc.)
You already know Python or you are ready to learn how to code.

ADDITIONAL INFO

At Carbon Maps we work:

Partly facetoface in our Paris office
Partly telecommuting with flexible hours
In a dynamic and committed team with varied profiles

We offer an internship bonus + a dematerialized meal ticket card + 50% of the Navigo pass.

Level of study required:
Master 1 and Master 2 (or equivalent).

ARE YOU INTERESTED IN THIS INTERNSHIP?

PROVE IT

Rather than a traditional cover letter, explain us in your own words, without fuss or formalism, how you would approach the following open (and difficult) question
: "How (choice of data, statistical models, etc.)

would you go about inferring the supply chain of a butter croissant based on Open Data ?"
Good luck