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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
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of biology and data science. if you can work independently and transparently manage and communicate data science projects. We offer you: a world-class research environment with state-of-the-art omics, high
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design are often too slow, costly, and inefficient to cope with the increasing complexity of performance and resource-efficiency requirements. This collaborative doctoral project brings together
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PhD Position in Theoretical Algorithms or Graph and Network Visualization - Promotionsstelle (m/w/d)
collaborations with academic partners like ETH Zurich, as well as companies and startups working on applied AI and high-performance computing. The entire curriculum and research infrastructure operate in English
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the entire spectrum of wet lab experimental work with the “state of the art” technics DNA, RNA, Protein work: isolation and analysis with PCR, qPCR, Western blot Immunofluorescence, microscopy, histology Cell
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together with a PhD student in the lab of Prof. Jeroen Krijgsveld, which will focus on the proteomics part of the joint SFB/CRC project applying state-of-the-art proteomic approaches, e.g. low-input/single
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University of Munich (TUM), you submit personal data. Please refer to our data protection information in accordance with Art. 13 of the General Data Protection Regulation (DSGVO): TUM Data Protection
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of experienced researchers from different institutes at Forschungszentrum Jülich. As one of Europe’s largest and most multidisciplinary research centers, Jülich offers access to state-of-the-art infrastructure and
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memristive devices, in collaboration with PGI-14. The goal is to train a system that leverages the intrinsic non-linear dynamics of these devices to perform complex learning tasks with extreme energy