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for the rapid conversion of biomass into hard carbons, significantly reducing the time and energy required compared to traditional processes. Additionally, the collaborative research aims to identify optimal
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formation and how local dose is distributed. In the longer perspective, this knowledge will support optimization and translation of bioelectronic implants towards clinical application. In this project, you
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such as satellites, LEO constellations, fixed links, automotive radar, and Earth observation stations, using techniques from signal processing, communications theory, optimization, and AI. You will join the
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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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the Ph.D. Our recent works on AI privacy and security: Practical Bayes-Optimal Membership Inference Attacks, NeurIPS 2025, https://arxiv.org/pdf/ 24089 Secure Aggregation is Not Private Against Membership
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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We are looking for a PhD student in Mineral Processing. As a PhD student, you will be part of an established international research group to work on a new research project, the optimization
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is to advance the understanding of forest ecosystems and how these should be managed today and in the future. For more information: http://www.slu.se/en/departments/forest-ecology-management/ Read more
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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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machine data analytics to new harvesting system designs. The Department of forest genetics and plant physiology is part of Umeå Plant Science Centre (UPSC, https://www.upsc.se ), a world leading centre for