22 Renewable-Energy scholarships in France

PhD Position : Planning of distributed renewable energy systems with machine learning

European environmental policies aim to significantly reduce, or even abandon, the use of fossil fuels, increase the share of renewable energies, and increase the electrification of uses, as with

PhD (M/F) in Optical control of electrocatalytic reaction mechanism for renewable energy storage

at the Institute of Physics of Rennes. We are a highly collaborative and international team with more than 20 researchers working in the areas of ultrafast spectroscopy, crystallography and energy conversion. Our

PhD (M/F) in Optical control of electrocatalytic reaction mechanism for renewable energy storage

at the Institute of Physics of Rennes. We are a highly collaborative and international team with more than 20 researchers working in the areas of ultrafast spectroscopy, crystallography and energy conversion. Our

PhD#4 at Mines Paris in Data Science & Energy: "Flexibility-aware forecasting of local energy demand"

of energy networks and the electrification of new usages that results in increasing demand by consumers (i.e. electric vehicles charging). Furthermore, the integration of high shares of renewables (wind

PhD in materials science (M/F)

the IHM (Hydrogen-Matter Interaction) team and will collaborate closely with the MC (Modeling Calculation) group. The energy transition towards renewable energies has become a priority. However, their

PhD#3 at Mines Paris in Data Science & Energy: "Seamless forecasting of local energy production and demand using multiple heterogeneous data sources"

and safe operation of modern power systems and electricity markets especially under high renewable energy sources (RES) penetration. The different contexts of application make that end-users require

PhD#5 at Mines Paris in Data Science & Energy: "Optimization of flexibility services under multiple local uncertainties in the context of smart grids"

of flexibility services under multiple local uncertainties in the context of smart grids" Context and challenges: In the context of the energy transition, power grids integrate massive amounts of renewable

PhD student position on modeling turbulent combustion of hydrogen/ammonia blends (M/F)

. Context: Gas turbine (GT) technology for power generation is and will be needed in the medium/long future to compensate for the intermittent output of renewable energy sources. GTs have been operated

PhD#2 at Mines Paris in Data Science & Energy: "High-dimensional optimization of distributed assets in smart grids"

the proliferation of assets connected to the grid, such as renewable energy (RES) plants, storage devices, electric vehicles (EVs), smart-homes/prosumers with IoT devices, electric heating/cooling

PhD#1 at Mines Paris in Data Science & Energy: "Artificial intelligence based prescriptive analytics for energy systems"

previous developments in this area in our Centre. These developments concern existing probabilistic forecasting methods for energy forecasting (demand, EVs demand, prices, renewable generation), as