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control and reinforcement learning supported by an edge-cloud-based wireless communication environment. The doctoral student will work on data-driven theory and method development in simulation environments
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description Trustworthy machine learning is an umbrella term that provides methods and tools to ensure that AI and ML systems are verifiable, robust, secure, privacy-preserving, and ethical, which leads
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methods in breast cancer diagnostics, with a particular focus on cancer screening and artificial intelligence. Located at the Skane University Hospital (SUS) Malmö, Diagnostic Radiology and LUCI are both
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group of scientists and medical professionals, mainly focused on innovative clinical imaging methods in breast cancer diagnostics, with a particular focus on cancer screening and artificial intelligence
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treatment method. We conduct research across a broad range of areas, including trauma, degenerative disease, pediatric orthopedics, and hand surgery. Depending on the research question, we employ a wide
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in both wet lab work and bioinformatics analysis of Oxford Nanopore long-read sequencing data related to X-linked diseases. Skilled in proteomic methods using MALDI-TOF and HPLC-MS, including data
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to study gene function in malaria parasites. The PhD student will apply scalable and innovative analytical methods to characterize the role of parasite genes during replication and host interactions
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independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your leadership and pedagogical skills. Throughout
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characterization (lithogeochemistry, XRD), and detailed microanalysis (e.g. SEM-WDS, electron microprobe, Raman spectroscopy, SIMS). The PhD student will integrate these methods to better understand how sedimentary
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funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with machine learning methods with the support of