Research Associate

We are a pioneering
Deep-Tech Battery Startup

, originating directly from a spin-off project at a leading university institute. Our mission is to revolutionize battery development, monitoring, and management using cutting-edge modeling and machine learning. We are seeking a highly motivated
Research Associate (m/f/d) in the Field of Modeling and Machine Learning for Battery Technology Applications

to join us as we transition from research into a start-up.

The position is initially limited to a duration of 2 years, with the possibility of extension thereafter. It offers the opportunity to become part of the spin-off project as well as the subsequent start-up.

Your Tasks

• Development of data-driven and physics-based battery models based on electrochemical impedance and voltammetry data in the time and frequency domains
• Contribution to the establishment and automation of a battery test bench
• Characterization of battery cells, modules, and systems
• Implementation of data-driven models using machine-learned models, particularly deep learning models and physics-informed neural networks

Your Qualifications

• You enjoy interdisciplinary research at the interface between computer science, electrochemistry, and sensor technology, and are eager to independently explore new and complex topics.
• You can develop, explain, and implement solutions independently and responsibly. You are adaptable, reliable, and a strong team player.
• You hold an above-average Master's degree (or equivalent) in one of the following fields: Computer Science, Electrical or Information Systems Engineering, Mechanical Engineering (Energy/ Process Engineering, Materials Science, Chemical Engineering), Chemistry/ Electrochemistry, or a comparable discipline.
• You have practical experience in at least two of the following areas: Electrochemical characterization of battery cells and interpretation of electrochemical impedance spectroscopy (EIS) data, Modeling of battery cells, Machine learning algorithms, in particular deep learning, Database systems (SQL/ NoSQL and/ or vector databases for AI applications)
• You have strong programming skills in at least one language, such as Python or MATLAB.
• Your expertise is demonstrated through prior work, e.g., a thesis, open-source projects, research experience in academia or industry, or professional experience.

Additional preferred qualifications:

• Experience with test-bench automation (e.g., LabVIEW)
• Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch)
• Knowledge of cloud computing and software deployment in cloud environments
• Very good knowledge of the German and English language

We also welcome your application if your background lies primarily in either electrochemistry or machine learning, provided you show a strong interest and are motivated to build expertise in the complementary area.

What We Offer

• Work on exciting future-oriented research topics in an inspiring work environment as part of the university community
• A vibrant campus life in an international atmosphere with lots of intercultural offers and international cooperations
• Payment in accordance with EG 13 TV-L
• Flexible working and part-time options and a family-friendly university culture
• Special continuing education programs for young scientists, as well as other offerings from the Central Personnel Development Department and sports activities

Apply by November 30, 2025

Application is only possible via the following link:

For more information, please reach out to us.

Further Notes

We welcome applicants of all nationalities. At the same time, we encourage people with severe disabilities to apply. Applications from severely disabled persons will be given preference if they are equally qualified. Please attach a proof of disability to your application.     We are also working on the fulfilment of the Central Equality Plan based on the Lower Saxony Equal Rights Act (Niedersächsisches Gleichberechtigungsgesetz, NGG) and strive to reduce under-representation in all areas and positions as defined by the NGG. Therefore, applications from women are particularly welcome.

Personal data will be stored for the purpose of processing the application. By submitting your application, you agree that your data may be stored and processed electronically for application purposes in compliance with the provisions of data protection law. Further information on data protection can be found in our data protection regulations at Application costs cannot be reimbursed.