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to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a suite of
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. The PhD will be within the respiratory and critical care group (rcare) at the Department of Health Science and Technology https://vbn.aau.dk/da/organisations/respiratory-and-critical-care-r-care. Here you
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on development of micro and nanotechnology-based sensors, detection systems, drug delivery and sampling devices, as well as energy materials for the gut. The job As a Research Assistant, you will work in close
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AI for Cyber-Physical Energy Systems (Copenhagen) The PhD position focuses on the development of secure and trustworthy AI for resource-constrained embedded systems used in power electronics and energy
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. Furthermore, the PhD candidate will engineer complex genotypes and perform adaptive laboratory evolution experiments. The candidate will work in an international team and is expected to contribute creatively
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contribute to the development of background-suppression techniques for single‑photon detectors used in axion experiments, operating at optical and infrared wavelengths. The research project includes
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PhD scholarship in Mid-Infrared Frequency Comb Technology for High-Sensitivity Sensing – DTU Electro
-sensitivity sensing applications. Your responsibilities will follow the project scope described above and include laser design and development, nonlinear frequency conversion, frequency-comb stabilization and
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). The successful PhD candidate will use a combination of adaptive laboratory evolution and rational metabolic engineering to achieve these goals. In addition, they will develop growth‑coupled selection strategies
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simulations and quantum chemical calculations. Interest in software development and automating computational workflows. Curiosity for understanding fundamental reaction mechanisms and atomistic processes
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working with deep learning software stacks, extensive software development experience, and knowledge of machine learning frameworks (such as transformers, torch, Megatron, triton etc.) are pluses. MSc