Postdoc Machine learning (IA) approach for Bio Feedstocks estimation M/F

Job title:

Postdoc Machine learning (IA) approach for Bio Feedstocks estimation M/F

Company:

TotalEnergies

Job description

Context & EnvironmentOneTech’s mission is to provide the technological and scientific expertise required to support development projects and operations across all TotalEnergies activities worldwide (oil and biofuels, natural and green gas, renewables and electricity). Its 3,400 employees – engineers, technicians, researchers, and support staff – are based on 9 sites across Europe and are fully committed to helping TotalEnergies achieve its ambition of becoming a major player in the energy transition, aiming for net zero emissions by 2050.Join our Customer Lines, Technical Lines, R&D Lines and Support functions teams, which assist all operational branches of TotalEnergies in their development projects and operational support!ActivitiesWithin TotalEnergies OneTech, the BioHub roadmap aims to provide competitive bio-based raw material alternatives for the production of biofuels (particularly SAF) that comply with current regulatory requirements and volume demands. Understanding the evolution of various factors such as climate change, the bio-based raw material supply chain, sustainable carbon use, and the management of agro-agricultural resources and non-recovered waste are key to producing aviation biofuels sustainablyQuantifying global Bio Feedstocks presents several challenges: data availability, high biomass variability and competition between different usages which can lead to inaccurate estimates. Furthermore, the existing studies and models concerning biomass availability are often difficult to compare, as they apply different criteria (e.g. technical, economic or sustainable) to overall potentials and these studies are not harmonized from one study to other nor always transparently documented.Aware of the importance of having reliable data on the availability of global biomass, the Upstream Bio Feedstocks team has developed an internal methodology to support TotalEnergies’ ambition in bio-based molecules and achieve carbon neutrality by 2050. However, it is critical to also estimate potential biomass availability at future horizons (e.g. 2030, 2040 or 2050) since this assessment may be integrated into TotalEnergies strategic portfolio.The Upstream Bio Feedstocks team from the Biofuels program is looking for a motivated postdoc scientist candidate to:

• Estimate biomass availability using a Machine Learning (AI) approach in real-time, including the use of open-source databases.
• Explore potential biomass using a Machine Learning (AI) approach while quantifying uncertainty and correcting biases at specific time horizons.
• Build dynamic spatial and temporal models.
• Communicate the methodology used and the results obtained within the department, to internal clients, partners, or others as necessary.
• Contribute to the acquisition of the intellectual property portfolio on topics related to the project.

Write reports or summaries based on the project.The position is based at Solaize (Lyon) and we propose a 18-month fixed-term private law contract to start in September 2025.The employment contract must be signed no later than three years after the date of obtaining the doctoral degree, in accordance with Article L.431-5 of the Research Code.Candidate ProfileThis position is for you if:

• You hold a PhD in Computer Sciences (less than 3 years) or equivalent practical experience or related technical field
• You demonstrated expertise in machine learning research
• You have strong mathematical skills, ability to formulate a research problem, design, implement and communicate solutions
• You are comfortable with modelling tools like Aspen, Python,
• You are fluent in English and French could be an option.
• You have good communication skills and you are able to work autonomous

Additional InformationTotalEnergies values diversity, promotes individual growth and offers equal opportunity careers.

Expected salary

Location

France

Job date

Fri, 16 May 2025 06:56:36 GMT

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