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/or student projects. Incidental expert (guest) lectures may be optional, whereas all primary teaching duties lie with our assistant, associate and full professors. Where to apply Website https
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Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing power, latency, and memory bandwidth issues with reliable
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to technical, legal and organizational constraints. As a PhD candidate, you will develop novel decision-making methods that enable robust decisions for heat transition planning despite these data-sharing
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future energy applications. Rather than simply implementing existing data space reference architectures, you will develop novel methods, architectural patterns, and engineering approaches that enable
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PhD candidate you will develop new ways to extract cosmic-ray physics from KM3NeT data. You will design and characterise reconstruction methods—both machine-learning-based and traditional
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to e‑wax), and long-term stability. By combining advanced kinetic studies with state-of-the-art operando characterization techniques, you will develop fundamental insights that enable improved catalyst
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of environmental biotechnology and engineering, systems microbiology, and computational biology, with ample opportunities to develop your own scientific ideas. Job requirements The ideal candidate will have the
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networking scenarios. You will analyze the combined FSO-RF-Fiber channel and develop accurate but sufficiently lightweight channel models and come up with jointly optimized schemes for such hybrid links and
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this highly interdisciplinary project, the PhD candidate will develop SERS-based strategies for targeted spatiotemporal detection and characterization of the fungal secondary metabolites, while closely
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) composition of the rejection water typically treated in these reactors. Develop and test mitigation measures in a full scale deammonification reactor. Pro-actively communicate your research findings with