Research/ Post doc position (H/F)
ABG-130333 | Emploi | Confirmé |
01/04/2025 | CDD 24 Mois | Salaire à négocier |

Employeur
The Center for Energy Efficiency of Systems (CES) is a research centre at MINES Paris, recognized as one of the key players in French research on energy efficiency and future energy systems. It currently has around 70 members and several dozen students (Master’s and post-masters students) spread across Paris and Satory.
In this research centre, our team on ecodesign and thermal simulation of buildings pioneered building LCA in the 1980s and developed ecodesign tools at the building and district scale. We contribute to the development of a building LCA tool distributed to professionals. We are coordinating the Lab Recherche Environnement (https://www.lab-recherche-environnement.org/en/ ), a research programme resulting from the partnership between VINCI and three ParisTech engineering schools supporting interdisciplinary research on the environmental performance of buildings, neighbourhoods and infrastructures.
Site web :
Poste et missions
Who we are looking for
We are looking for a talented and motivated young researcher to help us improve an eco-design tool for buildings and districts. You will collaborate on various research projects related to building and district life-cycle assessment, such as enhancing land-use evaluation in collaboration with ecologists and soil scientists or developing a method at the neighbourhood scale using spatialized data in collaboration with geomatic specialists.
Mobilité géographique :
Profil
Ideally, you
- Have Life Cycle Assessment (LCA) expertise, demonstrated through a relevant master degree, PhD thesis, postdoctoral experience, or impactful peer-reviewed publications.
- Hold a PhD in a field related to building energetics, Life cycle assessment, environmental sciences or engineering, or similar disciplines.
- Are proficient in computer programming, particularly in python
- Are a collaborative team player with a strong ability to work across disciplines.
- Demonstrate excellence in research with advanced quantitative data analysis and modelling skills.
- Possess excellent communication and presentation skills
- Are proficient in spoken and written English
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