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to collaboratively train machine learning models without sharing their data. Instead, clients exchange local model updates with a central server, which uses them to improve a global model. While this paradigm enhances
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the development of the I-Segmenter [1], a fully quantized ViT framework that achieves competitive accuracy while drastically reducing the inference cost. Internship Objective The objective of this internship is to
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:00 (UTC) Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Jan 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to
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wishes to develop work involving behavioural/experimental economics, in collaboration with energy economists. To this end, we are looking for a research associate who can help to drive forward this new