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An established industry player is seeking a research assistant to join their innovative Monitoring & AI department. This role focuses on developing and implementing cutting-edge AI and machine learning tools to monitor CO2 storage sites as part of a significant EU-funded project. You will utilize advanced platforms like TensorFlow and PyTorch to analyze complex datasets and enhance monitoring strategies. This position offers the opportunity to contribute to groundbreaking research while collaborating with national and international partners, all within a supportive and family-friendly work environment that values diversity and professional development.
City: Bochum
Date: Apr 10, 2025
Research assistant in Monitoring & AI for the EU-funded project "Eastern Lights"
The Fraunhofer-Gesellschaft (www.fraunhofer.com) currently operates 76 institutes and research units throughout Germany and is a leading applied research organization. Around 32 000 employees work with an annual research budget of 3.4 billion euros.
The Fraunhofer Research Institution for Energy Infrastructures and Geothermal Energy IEG conducts research at seven locations in the fields of integrated energy infrastructures, geothermal energy and sector coupling for a successful energy transition. Our research institute conducts applied research, develops innovative technologies for public and industrial clients and translates these into marketable products and processes.
The EU-funded “Eastern Lights” project will drive risk mitigation in large-scale carbon capture and storage (CCUS) in Eastern Europe. CO2 transport and underground storage will be de-risked by developing monitoring strategies and validating approaches in test facilities. Demonstration of an economically viable decarbonization pathway for the (cement) industry in Eastern Europe.
In the Monitoring & AI department, you will be involved in the development and implementation of AI and machine learning (ML) tools for monitoring and operation of CO2 storage sites. Key responsibilities will include utilizing state-of-the-art ML platforms such as TensorFlow and PyTorch to process and analyze complex datasets related to CO2 transport and storage. You will develop methods for real-time data transmission and processing, ensuring efficient and accurate monitoring of storage site conditions. Additionally, you will be responsible for creating and refining a real-time demonstration interface that provides operational insights. As the project progresses, you will continuously enhance the ML models to adapt to more sophisticated data, ensuring the tools remain at the cutting edge of the field.
We are looking for a research assistant specializing in Monitoring & AI at our Bochum location.
What You Will Do