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learning models achieve high performances on public datasets for single modalities, they are not adapted in practice. During this PhD project, the research will be focused on finding ways to integrate deep
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find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer
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these materials into high-performance fibers and functional materials. By manipulating molecular interactions through chemical and physical methods, we tailor the structural and mechanical properties of bio-based
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(MMICs); research on this will be performed in close co-operation between the University of Twente and TNO. You will be investigating the design of GaN HEMT MMICs in one of three positions. Depending
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understanding of protein systems. As a PhD student, you will: Design and perform fluorogenic and nano-photonic DyeCycling experiments. Write/adapt analysis code to process fluorescence trajectories and extract
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industry. The center offers an excellent working environment with access to state-of-the-art technologies and an outstanding high-performance computing infrastructure. For TUD diversity is an essential
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The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences | Poland | 6 days ago
person to: - Culture zebrafish embryos and larvae and perform genotypingthe - Perform experiments using zebrafish and cell cultures - Keep a record of experimental details - Participate in experimental
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applications towards materials science. Generative machine learning models have emerged as a prominent approach to AI, with impressive performance in many application domains, including materials discovery
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dynamics of these devices to perform complex learning tasks with extreme energy efficiency. Your Job: Develop and apply meta-optimization that can automatically search for the best algorithm-hardware pair
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and performing laboratory (wind-wave facility) experiments, using state-of-the-art imaging techniques developing computational codes to process and understand large experimental datasets (e. g., image