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(e.g., model compression/simplification and hardware-aware optimization). We are also interested in how resource-efficiency interacts with broader sustainability aspects of machine learning such as
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, hardware, implementation of the models in real environments and real-time testing. If you are more interested in such aspects, you are welcome to apply for the corresponding position which is going to be
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inference and deployment costs (e.g., model compression/simplification and hardware-aware optimization). We are also interested in how resource-efficiency interacts with broader sustainability aspects
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