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Field
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organisation To achieve valuable scientific results, talented PhD students need to acquire knowledge and are also required to exchange knowledge and experience with other PhD students in method-oriented working
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international conferences. This can provide opportunities for networking and learning from other researchers in your field. Extracurricular Seminars and Trainings The in-house umbrella organisation INGENIUM
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military or alternative service, to care for close relatives or due to long-term illness. Job hunting, unemployment and non-academic employment do not count as career breaks. The voluntary disclosure
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methods (such as Machine Learning, Metric Learning, Reinforcement Learning, Graph Representation Learning, Generative Models, Domain Adaptation, etc.) for Design Automation applications. To this end, we
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, Management Science, Business Analytics, or a related field. Strong analytical skills with experience in AI, machine learning, or data analytics. Very good English skills in writing and communication
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | 2 days ago
to conduct the thesis process, participate in lab visits, and learn according to their preferences or needs. A major focus of the curriculum is the flipped classroom concept, which increases students
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Humboldt Research Award programme information. Humboldt Research Award programme information (PDF, 63 KB) Recently selected award winners Hint Online info event: If you would like to learn more about this
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streaming and batch processing. These efforts provide the foundation for advanced analytics, machine learning, and AI applications. The IDE Research School guides PhD researchers by offering a platform for
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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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