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documentation of experimental results Preparation and publication of scientific articles in peer-reviewed journals Presentation of research results at international conferences and scientific meetings Your
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applications such as ferroelectric memory, photonic integrated circuits and next-generation telecommunications. You'll work at the exciting intersection of experimental materials science and materials
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methodological background in machine learning. The ideal candidate has demonstrated research experience with foundation models, including the evaluation and adaptation of pre-trained models, fine-tuning strategies
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, to quantify mediator-booster reactivity and component dissolution during operation, developing a firm understanding of how material formulation and experimental parameters govern charge transfer at the liquid