Thesis - Enhancing Machine Learning Transparency through Data Attribution
Stuttgart, DE, 70569
Fraunhofer-Gesellschaft
Die Fraunhofer-Gesellschaft mit Sitz in Deutschland ist die weltweit führende Organisation für anwendungsorientierte Forschung. Mit ihrer Fokussierung auf zukunftsrelevante Schlüsseltechnologien sowie auf die Verwertung der Ergebnisse in...Advertisement for subjects such as: all fields of study.
Explaining the predictions of ML models remains an important yet challenging task for the successful application of ML-based solutions, especially in safety-critical domains. A rather novel method is data attribution, where specific test predictions are attributed to the training data. We are interested in practical applications of these methods to ensure the safety and reliability of ML in real-world scenarios.
Was Sie bei uns tun
This thesis can take one of two directions: you can focus on the technical side and implement or improve current data attribution methods.
Alternatively, you can focus on the applied side and derive best practices and recommendations for the use of data attribution methods. In this case, you could conduct interviews with practitioners.
Was Sie mitbringen
- Experience in Python programming and the ability to write clean and well-structured code is necessary for the technical focus
- Prior experience with machine learning and common frameworks such as TensorFlow, PyTorch, or scikit-learn is a plus
- Knowledge of German is a plus
Was Sie erwarten können
- Opportunity to work at the intersection of research and industry within one of Europe's leading AI ecosystems
- Contribute to actual industrial projects with code that is implemented in real-world applications
- Employment as a research assistant (HiWi) for the duration of your thesis contract
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Mit ihrer Fokussierung auf zukunftsrelevante Schlüsseltechnologien sowie auf die Verwertung der Ergebnisse in Wirtschaft und Industrie spielt die Fraunhofer-Gesellschaft eine zentrale Rolle im Innovationsprozess. Als Wegweiser und Impulsgeber für innovative Entwicklungen und wissenschaftliche Exzellenz wirkt sie mit an der Gestaltung unserer Gesellschaft und unserer Zukunft.
Haben wir Ihr Interesse geweckt? Dann bewerben Sie sich jetzt online mit Ihren aussagekräftigen Bewerbungsunterlagen. Wir freuen uns darauf, Sie kennenzulernen!
Frau Jennifer Leppich
Recruiting
Tel. +49 711 970-1415
jennifer.leppich@ipa.fraunhofer.de
Fraunhofer-Institut für Produktionstechnik und Automatisierung IPA
Kennziffer: 72929
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Industrial Machine Learning ML models Python PyTorch Research Scikit-learn TensorFlow
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