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Field
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Transformers). Analysis of existing datasets. Evaluation of the trained models on suitable datasets. What you contribute Good knowledge in the field of machine learning and training neural networks. Good Python
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present. Evaluation of the trained models on suitable datasets. What you contribute Good knowledge in the field of machine learning and training neural networks. Good Python skills, preferably some
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Knowledge in the field of Machine Learning, including training, inference, and optimisation of transformer architectures. Knowledge in the field of ML security is desirable. Good Python skills, especially
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, exercise data and scripts (e.g., Bash, Python); creating exercise sheets and model solutions; conducting user tests Compiling new forensic datasets: researching or creating images, videos and text corpora
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mechanisms as well as the effectiveness and limitations of corresponding defense strategies. What you contribute Very good Python skills, which will be tested in the interview. Basic understanding of AI/ML
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) Familiar with basic terms and concepts such as: classification, hyperparameter optimization, fine-tuning, model evaluation Profound knowledge of Python is mandatory and will be tested in the interview
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-tuning, evaluation of models) Solid knowledge of Python is mandatory and will be tested in the interview Advantageous: ability to independently implement methods and procedures from scientific publications
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of software development (e.g., Java, C/C++, Python) and an interest in software security and AI Ideally, experience in areas such as static and dynamic program analysis, software engineering, or compiler
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Introduction to existing framework (PBRT-based simulation + Python code) Analysis of 3D results from simulation and physical experiments Prototyping, implementation, and test of software (Python, C++) Set-up and
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learning • Programming skills (e.g., Python, R) • Interest in interdisciplinary research at the intersection of data analysis and learning sciences • Interest in education and learning as an