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the BioImage Model Zoo platform and related cloud-based infrastructure Collaborating with interdisciplinary teams on the Reef - Automated Imaging Farm. Implementing AI and machine learning methods for Bioimage
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health. A concrete goal is to develop and design interpretable machine learning methods to predict and classify asthma and exacerbation of asthma. The aim is to improve respiratory health by designing
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to two doctoral students with a very strong background and interest in system modeling, optimization, and machine learning. The successful candidate will join a MSCA Doctoral Network project on developing
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on machine learning systems in PyTorch or JAX have experience in interpretable methods in machine learning have experience in using version control systems like Git and public repositories like GitHub
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evaluation of distributed systems and networks for machine learning inference. Supervision: Prof. Dejan Kostic What we offer The possibility to study in a dynamic and international research environment in
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made. The candidate should have strong research expertise from one or more areas: cloud computing and networking, machine learning/AI, statistics. We see that you have no problem collaborating with
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culture, isolation of cells from blood and tissue. Experience of image analysis, machine learning or related fields. Practical experience of programming. An interest in multi-disciplinary research
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an EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Machine Design The use of studded tyres during
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techniques for modern antenna-array based radar systems. Different techniques, including machine-learning, will be investigated for advanced digital, analog and hybrid beam-forming concepts, and applied
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Preferred qualifications Strong programming skills in Python, and other relevant languages (such as R) Background in AI, machine learning, data science, statistics, preferably with a focus on both statistical