PhD: Non-Destructive Battery Characterization & AI

Universidad de Deusto.; Bilbao; Presencial; EUR 25.751 - 31.473; Jornada completa

Descripción de la vacante

Universidad de Deusto in Bilbao invites applications for a doctoral grants call within the Deusto Smart Mobility Research Group (DeustoTech). The project explores non-destructive ultrasonic data collection from battery cells and applies AI methods to interpret the results.

You will contribute to research at the intersection of AI, ultrasonics and energy storage, support on-line manufacturing insights and sorting strategies for recycling.

Formación

• Programming skills in Matlab and/or Python.
• Strong analytical and problem-solving skills.
• Excellent knowledge of English (oral/written) is compulsory for the job profile and tasks development.
• Valuable items: knowledge of energy storage systems; experience with materials characterization; multidisciplinary environment experience; publications.

Responsabilidades

• Perform research at the intersection of Artificial Intelligence, ultrasonic technologies and batteries.
• Develop AI methods to leverage operando data for battery cell characterization and testing.
• Contribute to dissemination through conferences and publications; support at industrial applications and recycling processes.

Conocimientos

Matlab

Python

Analytical skills

English proficiency

Descripción del empleo

Universidad de Deusto in Bilbao invites applications for a doctoral grants call within the Deusto Smart Mobility Research Group (DeustoTech). The project explores non-destructive ultrasonic data collection from battery cells and applies AI methods to interpret the results.

You will contribute to research at the intersection of AI, ultrasonics and energy storage, support on-line manufacturing insights and sorting strategies for recycling.