• In-depth evaluation of different time-series prediction models (e.g. LSTMs, Transformers)      
• Research and evaluation of feature embedding methods
• Data engineering and feature augmentation (e.g. frequency decompositions)
• Implementation of a backtesting pipeline to estimate cost savings

• Extensive programming experience in Python 
• Good theoretical understanding of machine learning and deep neural networks
• Experience with time-series forecasting and commonly used prediction models is a plus

Are you looking for a multifaceted and intellectually stimulating position in a dynamic, cooperative and innovative work environment? Then LRZ is the place to be for you! Here at LRZ a collegial, appreciative work environment meets an international crowd of experts who work together to advance IT services for ground-breaking research. We offer flexible work schemes for an optimal work-life balance. Our staff values their creative leeway. As an institute of the Bavarian Academy of Science and Humanities we offer all the benefits of public service. And of course, no wishes remain unfulfilled at the LRZ in terms of technical equipment. We share experiences, constantly review and improve our processes, and are proud that our service-quality and data-security are regularly certified and rated highly.

We actively promote diversity and welcome applications from talented individuals, regardless of cultural background, nationality, ethnicity, gender and sexual identity, physical abilities, religion and age. We give priority to applications from people with disabilities who are equally qualified (SGB IX).   

We are looking forward to receiving your complete application documents (including cover letter, CV and certificates) in a PDF file (other file types are not accepted) by latest 24.11.2024.

Subject: Student Assistant (2024/48)

Are you unsure whether the job suits you or you suit us? Or do you still have questions about this position? Our colleagues will be happy to answer all your questions. 

This job does not fit? Then take a look at https://www.lrz.de/wir/stellen/ or send us an unsolicited application!

Here you will find information about the collection of personal data during the application process.