Graduate Assistant for Deep Learning Applications in Energy Reliability
vor 4 Wochen
Position Summary
We are seeking a skilled individual to become part of the team at Fraunhofer IEE in Kassel. Our focus is on enhancing the reliability and efficiency of energy systems through innovative methodologies. If you have a strong interest in data analysis and deep learning, this opportunity may be an excellent fit for you.
- Anomaly Detection: Transfer established techniques for anomaly detection from wind energy systems to other energy infrastructures, such as district heating systems. Assess their effectiveness in identifying operational faults.
- Explainable AI: Investigate and develop strategies to enhance the transparency of AI models, facilitating their integration into operational processes.
- Fatigue Load Modeling: Modify surrogate models to assess fatigue loads on wind energy systems, employing data-driven approaches that adhere to physical principles.
Qualifications
- Educational background in Computer Science, Mathematics, Physics, or related disciplines
- Familiarity with Machine Learning and Deep Learning techniques
- Experience with Tensorflow/Keras or PyTorch is advantageous
- Genuine interest in the reliability and optimization of energy systems
- Ability to work independently and demonstrate a proactive approach
What We Provide
- Engaging work on pioneering research topics with real-world applications
- Close collaboration with peers in research and administrative roles
- Excellent preparation for your future career
- Flexible working hours and support for your thesis
- Option for remote work
We embrace diversity within our team and encourage applications from individuals of all backgrounds. Candidates with disabilities will be given preference if equally qualified. The monthly workload ranges from 60 to 80 hours, and compensation aligns with the overall agreement for student employees.
Fraunhofer-Gesellschaft plays a pivotal role in driving innovation in essential technologies and shaping our future. Join us in making a difference with your expertise and commitment.
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