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Field
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private machine learning: Differential privacy (DP) is the gold-standard for privacy protection, but deep learning models trained with DP suffer from privacy-utility trade-offs. You will develop novel model
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subjects, high interdisciplinary desire to learn, and willingness to cooperate, openness for internationalization and diversity, very good verbal and written English communication skills (good command
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internships Not required by the IMPRS-ESM Teaching/work obligations or opportunities There is no obligation to teach. However, if desired, positions as teaching assistant can be searched for. Special promotion
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tools for distributed models, and iii) robustness to data and model poisoning attacks. In this context, we are looking for a PhD Candidate who has a strong background in machine/deep learning to push our
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tools for distributed models, and iii) robustness to data and model poisoning attacks. In this context, we are looking for a PhD Candidate who has a strong background in machine/deep learning to push our
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.) Knowledge of machine learning, data mining, or related fields Excellent communication skills and ability to work in a collaborative team environment Interest in social science research methods and theories
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evaluating machine-learning models. Expertise in in the field of Building Information Modelling and geometric modelling is greatly beneficial. Excellent English and the willingness to learn the German language
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for this position, the candidate should possess in-depth skills in programming and hands-on training and evaluating machine-learning models. Expertise in in the field of Building Information Modelling and geometric
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Linguistics, Data Science or a similar field Good theoretical knowledge and practical experience with Natural Language Processing (rule-based and/or machine learning) Software Engineering Motivation to build