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Field
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the domain of digitalisation and energy renovation. You will learn to conduct research independently and grow scientifically through collaboration and supervision by researchers from Saxion and Hanze
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networks, or network science, and relevant background knowledge n methods in machine learning and AI. The successful candidate will focus on innovating the field of network analysis with AI methods. Examples
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research, as evidenced by its participation in various international research collaborations. Additional information Feel free to contact us if you want to learn more about the vacancy: Dr. Sascha van
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X-ray spectroscopy, methane isotopes, metagenomics and transcriptomics), combined with reactive transport modelling. Your teaching load may be up to 10% of your working time. Would you like to learn
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leveraged a culture of open, collaborative innovation to scale the reach of our ideas and pace of iteration, without having to scale our headcount. We operate in Chicago, New York, and Amsterdam. In our
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team-based scientific research, producing publications for national and international forums, contributing to the further development of the DNPP website and helping to acquire external research funds
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technologies. The successful candidate will have strong data-driven methodological learning opportunities with high social impact on cancer care organisation. They will work within an interdisciplinary team
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from individuals of all backgrounds and experiences. Your unique perspectives will enrich our research and foster a collaborative and innovative environment. Research at our faculty Leiden University is
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. Project 2. Project title: Motor learning as a window into neurodegeneration: an interdisciplinary approach Supervisors Dr Defne Abur (YAG, Faculty of Arts, Assistant Professor of Speech and Speech
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be part of a collaborative and inclusive team of around 35 scientists, where personal growth, professional development, and a strong sense of community are highly valued. You will contribute