Student Assistant: ML applications in Digital Twin Development in Offshore Wind Energy

Fraunhofer-Gesellschaft; Kassel; Hybrid; Teilzeit

Zusammenfassung

A leading research institute in Kassel is seeking a master's student to assist in developing AI models for energy forecasting in offshore wind farms. The role offers insights into application-oriented research and potential for future employment. Candidates should be pursuing a degree in a relevant field and possess strong programming skills. Opportunities for flexible working hours and thesis topics are available.

Leistungen

Flexible working hours

Access to expert networks

Opportunity for thesis

Commitment to diversity and inclusion

Qualifikationen

• Currently pursuing a master's degree in a relevant field.
• Strong interest in wind energy development.
• Experience with time series data is advantageous.

Aufgaben

• Assist in developing and validating AI models for energy forecasts.
• Extract insights from large datasets using AI techniques.
• Collaborate to develop innovative forecasting algorithms.

Kenntnisse

Proficient in Python

Strong analytical skills

Team spirit

Excellent communication in English or German

Ausbildung

Master's degree in Data Science, Applied Mathematics, Computer Science, Physics, Meteorology, or a related field

Tools

Machine learning/statistical methods

Databases

Containerization

MLOps knowledge

Jobbeschreibung

Overview

The Fraunhofer IEE in Kassel conducts research in energy management and energy system technology, focusing on energy informatics, energy meteorology and geoinformation systems, energy management and system design, energy process engineering and storage, grid planning and operation, grid stability and power conversion technology, and thermal energy technology. Around 450 scientists, employees and students develop solutions for the energy transition and generate around 40 million euros in revenue per year.

Would you like to help shape the implementation of the energy transition and work at the interface between science and industry?

What you will do

• Assist in the development and validation of advanced AI and statistical models for energy forecasts in offshore wind farm digital twins.
• Utilize AI and statistical techniques to extract insights from large time series datasets.
• Collaborate within an interdisciplinary team to develop innovative algorithms for forecasting, ranging from short-term to seasonal predictions.
• Create prediction modules for digital twins and support their deployment using containerization technologies.

What you bring to the table

• Currently pursuing a master’s degree in data science, Applied Mathematics, Computer Science, Physics, Meteorology, or a related field.
• Strong interest in wind energy development and the energy transition.
• Proficient in Python or similar object-oriented programming languages.
• Experience with machine learning/statistical methods applied to time series data is advantageous.
• Familiarity with databases, containerization, and knowledge of MLOps is a plus.
• Goal-oriented with strong analytical skills, team spirit, and excellent communication in English or German.
• Independent, self-motivated, and enthusiastic about interdisciplinary collaboration.
• Interest in scientific research and the potential for a master’s thesis.

What you can expect

• Insight into application-oriented research in the energy sector with direct relevance for industry and society
• Access to expert networks in the energy industry and research
• Commitment to the Diversity Charter – we actively promote diversity and inclusion in all areas
• Optional opportunity to write a bachelor’s or master’s thesis on a topic of your choice
• Prospects for future permanent employment or doctoral studies
• Flexible and individual adjustment of working hours to lecture and exam times, as well as the option to work from home or in a modern institute building with a New Work concept in a central location

The monthly working hours are between 40 and 80 hours. The position is initially limited to 12 months; longer-term employment is hoped for. Exceptions to a shorter term are for fundamental operational reasons, the personal wishes of the student, or the end of their studies.

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.

Fraunhofer plays a central role in the innovation process, focusing on developing key technologies for the future and enabling commercial utilization by business and industry. Fraunhofer aims to shape society now and in the future.

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

Questions for this job can be directed to:

• Abhinav Tyagi (Tel: [phone])

Fraunhofer Institute for Energy Economics and Energy System Technology IEE

www.iee.fraunhofer.de

Requisition Number: 81485