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in the CBSC focused on ligand discovery, joining a team of dedicated computational researchers with diverse expertise ranging from structural bioinformatics to machine learning and AI. Your primary
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machines into the cellular context in space and time, how stress factors influence these processes, and how the cellular network enables their robust functioning. Research Focus 3 Microbes providing
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lit. b (postdoc) Limited until: 28.02.2030 Reference no.: 4889 Among the many good reasons to want to research and teach at the University of Vienna, there is one in particular, which has convinced
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cutting-edge research in areas such as pattern recognition, automation science, complex systems, AI for Science, robotics, machine learning, computer vision, natural language processing, biometrics, medical
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on their potential and demonstrated skills in teaching and research. The candidates should have a solid background or experience in multi-omics data analysis, including, for example, machine learning. Additionally
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publication record relative to their career stage and a clear interest in interdisciplinary collaboration. Ideally, you also bring experience with machine-learning or hybrid modelling approaches, as
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principles that regulate host-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put
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teaching are required. A successful candidate will be expected to teach courses at the graduate and undergraduate levels and to build and lead a team of graduate students in PhD research. Applications should
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(I3S), Sophia Antipolis Hosting lab: I3S & INRIA UniCA Apply by sending an email directly to the supervisor: emanuele.natale@univ-cotedazur.fr Primary discipline: Machine Learning Secondary discipline
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experience prior to pursuing a PhD or graduate program, offering exceptional mentorship, training, and professional development in a world-class research setting. Research Technicians from the Ruta Lab have