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PhD CIFRE RTE - MINES PARIS: Artificial Intelligence for Renewable Energy Forecasting - Job Opportunity at Mines Paris - PSL & RTE

Paris, France
Full-time
Entry-level
Posted: April 26, 2025
On-site
EUR 30,000-35,000 per year (standard CIFRE contract)

Benefits

CIFRE doctoral contract providing industry-standard PhD funding
Collaboration between academic and industry sectors
Access to advanced research facilities
Industry networking opportunities
Professional development through RTE's corporate environment

Key Responsibilities

Develop advanced AI-based forecasting methods for renewable energy generation
Analyze and process large-scale datasets from distributed RES plants
Design and implement multi-scale forecasting models
Conduct comprehensive literature reviews using AI-assisted approaches
Validate and benchmark new forecasting solutions against existing methods
Collaborate with both academic researchers and industry professionals

Requirements

Education

Engineer and/or Master of Science degree

Required Skills

Applied mathematics, statistics and probabilities Data science, machine learning, artificial intelligence Energy forecasting Programming (Python) Good analytical, synthesis, innovation and communication skills Good level in French Excellent level in English
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Sauge AI Market Intelligence

Industry Trends

The renewable energy forecasting sector is experiencing rapid growth due to increased RES integration, with an estimated 20-30% annual increase in demand for AI-based solutions Major power utilities are investing heavily in AI/ML capabilities, creating a specialized niche for experts in this domain Grid operators worldwide are facing similar challenges, making this research globally relevant and transferable

Role Significance

Typically working within a research team of 5-10 members, plus industry collaborators from RTE
Entry-level research position with significant strategic importance due to direct industry application

Key Projects

Development of next-generation forecasting systems for national grid operations Integration of multi-source data for improved prediction accuracy Creation of scalable AI solutions for renewable energy management

Success Factors

Deep understanding of both theoretical AI concepts and practical energy systems Ability to bridge academic research with industrial applications Strong mathematical foundation combined with programming expertise Effective communication skills for collaborating with diverse stakeholders

Market Demand

Very high demand for AI specialists in renewable energy, particularly in European markets due to aggressive decarbonization targets

Important Skills

Critical Skills

Advanced AI/ML expertise with focus on large-scale time series forecasting Strong mathematical foundation for complex model development Programming skills for implementing scalable solutions

Beneficial Skills

Knowledge of power systems and grid operations Experience with weather data processing Familiarity with energy markets and regulations

Unique Aspects

Direct access to national-scale energy data and infrastructure
Combination of academic research with immediate industrial application
Potential to impact national energy transition strategies
Exposure to both research and operational aspects of energy systems

Career Growth

3-year PhD program with potential for immediate industry position upon completion

Potential Next Roles

Senior Data Scientist in Energy Companies Research Scientist in Renewable Energy Technical Lead for Energy Forecasting Systems Energy Analytics Consultant

Company Overview

Mines Paris - PSL & RTE

Collaboration between France's premier engineering school and national grid operator, combining academic excellence with real-world application

Leading position in French energy research and grid operation sectors
Central role in European energy transition research and implementation
Hybrid academic-industrial environment fostering innovation and practical application
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