Deep-Learning Weather Prediction Engineer (H/F)

TOTAL Deutschland GmbH; Palaiseau; Sur place; EUR 65 000 - 90 000; Plein temps

Résumé du poste

TOTAL Deutschland GmbH seeks a talented professional to join their Integrated Power Modeling initiative focused on weather forecasting. The role involves developing deep learning solutions to support strategic decision-making and competitiveness in energy systems.

The ideal candidate holds a Master's or PhD in deep learning, has over 6 years of experience, and is fluent in both English and French. Responsibilities include designing workflows and collaborating with various stakeholders.

Qualifications

• Master's or PhD in deep learning with a specialization in meteorological modeling.
• Hands-on knowledge of deep learning-based weather forecasting models.
• Practical knowledge of prerequisites for industrializing deep learning.

Responsabilités

• Support short- and medium-term commercial ambitions in weather forecasting.
• Design and develop robust internal workflows based on deep learning solutions.
• Conduct both industrial and academic monitoring to stay at the forefront of weather forecasting technologies.

Connaissances

Deep learning-based weather forecasting models

Hands-on knowledge of meteorological data

Practical knowledge of industrializing deep learning

Proficiency in cloud and HPC infrastructures

Fluent in English

Fluent in French

Formation

Master's or PhD in deep learning with specialization in meteorological modeling

Outils

GraphCast

Aurora

FourCastNet

Description du poste

TotalEnergies has launched an ambitious Integrated Power Modeling initiative designed to secure a leading position in nextgeneration energy systems and electricity markets.

As renewable energy sources are increasingly integrated into power grids andindustries, transportation, and buildings undergo large-scale electrification, the energy landscape is evolving at an unprecedentedpace.

In this context, advanced modeling and forecasting solutions to support supply-demand balance management have becomecritical enablers of strategic decision-making and long-term competitiveness.

• Support short- and medium-term commercial ambitions in weather forecasting
• Collect and acquire the most relevant datasets both open-source and proprietary tailored to specific geographical areas
• Design and develop robust internal workflows based on deep learning solutions
• Continuously integrate and evaluate the latest models from major tech companies, startups, and academia
• Create educational content adapted for a general audience
• Produce scientific documentation to explain internal developments and contribute to scientific conferences
• Provide support for the adoption and use of internal forecasting tools within the organization
• Conduct both industrial and academic monitoring to stay at the forefront of weather forecasting technologies
• Identify and collaborate with stakeholders at all levels: academia, industry, business units, and programs
• Contribute to team skill development through training, workshops, and knowledge-sharing initiatives
• Master's or PhD in deep learning with a specialization in meteorological modeling.
• Hands-on knowledge of deep learning-based weather forecasting models such as GraphCast, Aurora, and FourCastNet.
• Hands-on knowledge of the most relevant input data for weather forecasting: meteorological agencies, satellite imagery, and local observations.
• Practical knowledge of the prerequisites for industrializing deep learning.
• Proficiency in computing infrastructures, both cloud and HPC including Slurm, as well as storage architectures.
• More than 6 years of professional experience.
• English and French required.