Fraunhofer-Gesellschaft
Masterarbeit: Robustheit von Autorschaftsverifikation gegenüber Adversarial Obfuscation(m/w/x)
Full-timeTemporary contractOn-siteNot specified
Darmstadt
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FRFraunhofer-Gesellschaft
Master's Thesis: Robustness of Authorship Verification against Adversarial Obfuscation(m/w/x)
Darmstadt
Full-timeOn-site
AI/ML
Data Science
Nejo AI Summary
Implementing and evaluating style obfuscation attacks for robust Authorship Verification at an application-oriented research organization. Knowledge in ML, NLP, Transformer models, and Python with PyTorch/HuggingFace experience needed. Independent work schedule.
Requirements
- Knowledge in Machine Learning, ideally NLP and Transformer models
- Good Python skills, preferably PyTorch or HuggingFace experience
- Scientific interest in robustness, security, and evaluation metrics in AI systems
- Motivation for adversarial attacks and modern AV approaches
Tasks
- Implement and evaluate style obfuscation attacks.
- Research and implement robust Authorship Verification (AV) methods.
- Perform self-critical evaluation.
- Compare findings with baselines on benchmark datasets.
- Present results and discuss weaknesses of current methods.
- Measure attack impact on common AV models.
- Design robust defense procedures.
- Apply adversarial training or contrastive learning for defense.
Education
- Currently in higher educationOR
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- HuggingFace
Benefits
Flexible Working
- Independent work schedule
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Fraunhofer-Gesellschaft and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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FRFraunhofer-Gesellschaft
Master's Thesis: Robustness of Authorship Verification against Adversarial Obfuscation(m/w/x)
Darmstadt
Full-timeOn-site
AI/ML
Data Science
Nejo AI Summary
Implementing and evaluating style obfuscation attacks for robust Authorship Verification at an application-oriented research organization. Knowledge in ML, NLP, Transformer models, and Python with PyTorch/HuggingFace experience needed. Independent work schedule.
Requirements
- Knowledge in Machine Learning, ideally NLP and Transformer models
- Good Python skills, preferably PyTorch or HuggingFace experience
- Scientific interest in robustness, security, and evaluation metrics in AI systems
- Motivation for adversarial attacks and modern AV approaches
Tasks
- Implement and evaluate style obfuscation attacks.
- Research and implement robust Authorship Verification (AV) methods.
- Perform self-critical evaluation.
- Compare findings with baselines on benchmark datasets.
- Present results and discuss weaknesses of current methods.
- Measure attack impact on common AV models.
- Design robust defense procedures.
- Apply adversarial training or contrastive learning for defense.
Education
- Currently in higher educationOR
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- PyTorch
- HuggingFace
Benefits
Flexible Working
- Independent work schedule
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Fraunhofer-Gesellschaft and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
Fraunhofer-Gesellschaft
Industry
Research
Description
Das Unternehmen ist eine der führenden Organisationen für anwendungsorientierte Forschung mit 76 Instituten in Deutschland.
Not a perfect match?
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