Researcher (R2.1) in the Field of Energy Storage and Artificial Intelligence
IREC - Catalonia Institute for Energy Research
Barcelona, Spain
Description:
The Nanoionics and Fuel Cells team is a dynamic research group dedicated to advancing solid-state energy conversion technologies. We are currently seeking a postdoctoral researcher (R2.1 level) specializing in high-throughput materials discovery for energy storage applications. The offer consists of a tenure track position and offers an opportunity to contribute to cutting-edge research in electrochemical energy storage, particularly in areas such as Zn-air technology, through advanced high-throughput materials exploration techniques.
The appointed researcher will be responsible for:
- Developing and fabricating samples that span extensive compositional spaces.
- Designing and implementing automated characterization processes.
- Creating and applying machine learning models to analyze data for high-throughput materials exploration.
The primary goal of this research is to establish innovative AI-driven procedures to rapidly identify new, high-performance, and stable energy materials.
Qualifications and experience required:
Essential:
The call is open to professionals from any nationalities that fulfil the following eligibility criteria:
- Hold a PhD in the areas of Physics, Chemistry, Material Engineering & Science, Chemical engineering, or related areas.
- Experience in the field of energy and electrochemistry.
- Experience in AI-assisted data analysis.
- Fluent in English.
Preferred:
- Knowledge in thin film fabrication technologies.
- Knowledge and experience in projects in the energy sector, especially in electrochemical energy storage, advance materials for energy.
- Good communication skills; ability to communicate complex scientific information to individuals from other disciplines.
- Experience in collaborative research projects.
- Energy materials-related scientific publications.
Personal Skills:
- Team Worker.
- Initiative in Research and Innovation.
- Flexibility.
- Results-oriented.
- Analytical and synthesis capabilities.
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