Research Assistant for Determining the Remaining Useful Lifetime of EV Batteries

Fraunhofer-Alumni e.V.; Bochum; Vor Ort; EUR 40.000 - 60.000; Vollzeit

Zusammenfassung

A leading research organization in Bochum seeks a Research Assistant to contribute to an EU-funded project on battery technology. The role involves literature research and model development for predicting the Remaining Useful Lifetime of batteries. Candidates should be Master's students in relevant fields with programming and machine learning experience, who are eager to engage in applied research and innovation in energy solutions.

Leistungen

Flexible working hours

Well-equipped technical infrastructure

Opportunity to combine work with Master's thesis

Diverse and interdisciplinary working environment

Qualifikationen

• Matriculated Master's student in relevant fields.
• Profound knowledge of programming, preferably Python.
• Practical experience with machine learning frameworks.

Aufgaben

• Conduct literature research on RUL of batteries.
• Implement and experiment with RUL prediction models.
• Document methods, results, and findings thoroughly.

Kenntnisse

Programming

Machine Learning

Deep Learning

Data Analysis

Communication Skills

Ausbildung

Master's degree in Electrical Engineering, Data Science, Computer Science, Physics or related field

Tools

Keras

PyTorch

Jobbeschreibung

City: Bochum

Date: May 13, 2025

Research Assistant for Determining the Remaining Useful Lifetime of EV Batteries

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 Geotechnologies IEG conducts research at seven locations in the fields of integrated energy infrastructures, geothermal energy and sector coupling for a successful energy transition. Our institute conducts applied research, develops innovative technologies for public and industrial clients and translates these into marketable products and processes.

Our competence center for “Monitoring and Artificial Intelligence” researches and develops innovative AI and monitoring methods across numerous fields of energy infrastructures and geothermal energy systems. We develop and use AI-based applications with a focus on the development of analytical methods for the analysis of large data sets, feature extraction, automatic pattern recognition, anomaly detection and predictive analytics.

The aim of the BASE project is to develop a trustworthy and interoperable framework for the Digital Battery Passport (DBP) to ensure traceability and sustainability in the battery value chain. The DBP will provide up-to-date and accurate data on battery performance indicators, remaining useful life, disassembly, material composition and safety.

More information on BASE: Nur die transparente Batterie wird grün

We are looking for a research assistant to support us at our location in Bochum.

What You Will Do

• You will conduct literature research on modern approaches for predicting the Remaining Useful Lifetime (RUL) of batteries.
• You will implement and experiment with different RUL prediction models using data-driven and physical methods.
• The evaluation and comparison of these models are also on your agenda.
• In addition, you will analyze, evaluate and compare the models to identify strengths, limitations and areas for improvement.
• Thorough documentation of the methods, results and findings is also required.
  
  

What You Bring To The Table

• Matriculated Master's student majoring in electrical engineering, data science, computer science, physics or a related field.
• Profound knowledge of at least one programming language, preferably Python.
• Previous experience in machine learning and deep learning.
• Practical experience with frameworks such as Keras or PyTorch
• Good written and oral communication skills in German and English.
  
  

What You Can Expect

• You will work as part of a diverse and interdisciplinary consortium on a large EU-funded research project.
• You will have the opportunity to combine your work with a Master's thesis, supported by experienced scientists.
• In addition, you will gain insights into applied AI methods for real-world applications and challenges.
• A practice-oriented and future-oriented work activity
• Our supervisors make you strong so that you are successful
• Flexible working hours that fit in with your studies
• Well-equipped technical infrastructure at your workplace
  
  

We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. Remuneration according to the general works agreement for employing assistant staff.

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future.

Interested? Apply online now. We look forward to getting to know you!

We will be happy to answer any questions you may have about this position:

Dr. Shahin Jamali and Dr. Noah Biederbeck

via E-Mail

Questions About The Application Process Will Be Answered By

Herr Philipp Steinborn

Tel: [phone]

via E-Mail

Fraunhofer Research Institution for Energy Infrastructures and Geotechnologies IEG

www.ieg.fraunhofer.de

Requisition Number: 79763 Application Deadline: 06/15/2025

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