Engineer (f/m/d) - Analysis and optimization of solid-state batteries

German Aerospace Center (DLR); Ulm; Vor Ort; EUR 50.000 - 70.000; Teilzeit

Benefits dieser Stelle

Diversity and equality promotion

Training and development opportunities

Zusammenfassung

The German Aerospace Center (DLR) in Ulm seeks a Researcher for machine learning-based simulations in energy storage. Responsibilities include developing workflows for digital twins of electrode materials, predicting capacity loss, and optimizing solid-state battery designs. Candidates should have a Master’s in Engineering, Physics, Chemistry, or Mathematics, with strong analytical skills and programming expertise in Python. DLR values diversity and offers numerous training opportunities for personal and professional development.

Qualifikationen

• Excellent analytical skills demonstrated by a master’s degree.
• Strong expertise in machine learning.
• Very good programming skills in Python.

Aufgaben

• Development and research on machine learning-based workflows.
• Optimizing material and electrode designs for solid-state batteries.
• Collaborating with experimental partners on battery designs.
• Presenting results at conferences and publishing in journals.

Kenntnisse

Analytical skills

Machine learning expertise

Knowledge of physical process modeling

Programming skills in Python

Independent work style

Proficient in English

Ausbildung

Master’s degree in Engineering, Physics, Chemistry or Mathematics

Jobbeschreibung

Overview

Vacancy-ID: 4886

Place of work: Ulm

Starting date: 01.07.2026

Career level: Doctorate

Type of employment: Part time; Full-time

Duration of contract: 3 Jahre

Remuneration: Remuneration is in accordance with the Collective Agreement for the Public Sector - Federal Government (TVöD-Bund)

Short Description of Institute/Facility - At the Institute of Engineering Thermodynamics we investigate the energy storage systems of today and tomorrow.

The Department of Computational Electrochemistry located at the Helmholtz Institute Ulm for Electrochemical Energy Storage (HIU) develops new theories and tools for the simulative investigation of battery materials and cells. As a member of an internationally leading research team in the field of battery simulation, you will make, together with our partners in industry and academia, an important contribution to the understanding and optimization of this key technology. We offer you an attractive environment to conduct your cutting-edge research, room for your own ideas and the possibility to receive a PhD.

Your tasks

• Development and research on machine learning-based workflows for generating digital twins of electrode materials and performing virtual analyses of aging mechanisms using physico-chemical models
• Predicting failure patterns and capacity loss using physics-informed machine learning approaches
• Optimization of material and electrode designs for solid-state batteries
• Collaboration on projects with experimental partners to investigate, optimize, and validate solid-state battery designs
• Presentation of the results at conferences and publication in scientific journals

Your Skills

• Excellent analytical skills demonstrated by a master’s degree in Engineering, Physics, Chemistry or Mathematics
• Strong expertise in machine learning
• Profound knowledge of the theory, modeling and simulation of physical processes
• A strong motivation to develop theories and digital tools and put them into practice
• Very good programming skills in Python
• Independent and results-oriented style of working
• Passion for innovative research
• Proficient English language skills

We offer

DLR stands for diversity, appreciation and equality for all people. We promote independent work and the individual development of our employees both personally and professionally. To this end, we offer numerous training and development opportunities. Equal opportunities are of particular importance to us, which is why we want to increase the proportion of women in science and management in particular. Applicants with severe disabilities will be given preference if they are qualified.

We look forward to getting to know you!

If you have any questions about this position (Vacancy-ID 4886) please contact:

Dr. Timo Danner
Tel.: [phone]