Academic Researcher (f/m/d)

Karlsruhe Institute of Technology (KIT); Eggenstein-Leopoldshafen; Vor Ort; EUR 50.000 - 60.000; Vollzeit

Benefits dieser Stelle

Science for Impact

Career-building opportunities

Flexible hours

Family-friendly

Wellbeing program

JobTicketBW contribution

Zusammenfassung

Karlsruhe Institute of Technology (KIT) is offering a PhD-position focusing on coordinating flexible facilities using reinforcement learning in smart grids. You will design models, run simulations, and contribute to publishing results while potentially assisting in teaching at KIT’s Energy Lab and Campus North grid.

The role requires a Master’s in a relevant field, strong ML/Stats knowledge, programming ability, and excellent English.

Qualifikationen

• Completed master’s degree in a relevant field (CS, ME, Math, IE&M or comparable).
• Excellent knowledge in Machine Learning and statistics.
• Solid expertise in energy informatics and electrical engineering.
• Strong understanding of stochastic processes/probability theory.
• Programming experience required.
• Excellent written and spoken English skills.
• Strong teamwork and communication skills, willingness to learn, solution-oriented.

Aufgaben

• Research topics in smart grids and virtual power plants; identify research gaps.
• Design models and algorithms, and perform programming.
• Implement solutions in simulations and on KIT Energy Lab hardware.
• Conduct experiments, analyze results, derive insights.
• Publish results in academic journals and conferences.
• Assist with teaching.

Kenntnisse

Machine Learning

Statistics

Programming

Energy informatics

Electrical engineering

Stochastic processes

English proficiency

Teamwork

Ausbildung

Master’s degree in Computer Science

Master’s degree in Mechanical Engineering

Master’s degree in Mathematics

Master’s degree in Industrial Engineering and Management

Jobbeschreibung

Responsibilities

A major challenge of the energy transition is managing variable electricity generation from renewable energy sources and coordinating it with storage systems and flexible consumers. The bundling of flexible or controllable facilities within virtual power plants, intelligent districts, or as intelligent areas is a central approach to reducing system complexity. The goal of this position is the conception, implementation, evaluation, and testing of new solutions for coordinating flexible facilities. The focus lies on the application of reinforcement learning and the consideration of stochastic influences Specifically, you will have the following responsibilities:

• Researching and familiarizing yourself with the topics of smart grids and virtual power plants, as well as the current state of the art, and identifying research gaps
• Designing models and algorithms, as well as programming
• Implementing the solutions in computer simulations and subsequently using the Energy Lab’s actual hardware and the Campus North grid
• Conducting experiments, analyzing the results, and deriving new insights
• Publishing the results in academic journals and at conferences
• Assistance with teaching

In addition to research activities, there is the opportunity to pursue a Ph.D.

Your Profile

• A completed master’s degree in computer science, mechanical engineering, mathematics, Industrial Engineering and Management or a comparable field of study
• Excellent knowledge in the fields of Machine Learning and statistics
• Solid expertise in the areas of energy informatics and electrical engineering
• Strong understanding of stochastic processes/probability theory
• Programming experience
• Excellent written and spoken English skills
• Strong teamwork and communication skills, a strong willingness to learn, and a solution-oriented approach to work

We Offer

• Science for Impact : Engage with topics of societal relevance—in an excellent scientific environment that enables change.
• Career‑Building and Developmental Opportunities : We provide you with a structured onboarding program, a broad spectrum of continuing‑education options, and personalised support, thereby fostering your individual growth.
• Flexible Working Hours : Take advantage of flexible‑hours schemes, remote‑work options, and a 30‑day annual leave entitlement to achieve an optimal work‑life balance.
• Family-friendliness : The “KIT‑Family+” program assists you in reconciling work and family life by offering childcare services, holiday activities, a parent‑child office space, and assistance with caring for relatives.
• Stay Healthy : Under the motto “Fit at KIT – Body, Mind and Soul,” we promote your well‑being through fitness classes and mental‑health programmes.
• Individualised Extra Benefits : Enjoy a corporate pension (VBL), a €25 monthly contribution toward a JobTicketBW, plus a broad selection of cultural and recreational programmes.

Job location

Eggenstein-Leopoldshafen (and Karlsruhe)

Salary

Salary category 13 TV-L; classification is based on personal and professional qualifications.

Contract duration

3 years

Contact person in line-management

Dr. Kevin Förderer

[e-mail]

[phone]

If you have general questions about the application process, please contact

Katja Wenz

Personalservice (PSE)

[e-mail]

[phone]

At KIT we value the diversity of our employees; different perspectives and backgrounds enrich our work. We therefore welcome applications from all candidates. Women are especially encouraged to apply. Applications from recognized severely disabled individuals are given preferential consideration when qualifications are equal.

Application up to: 2026-10-23

Job posting number: 371/2026