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Autonomous Scalable Knowledge Extraction and Decision Making for Complex Systems and Dynamic Environments School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof
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process, modification of the microenvironment components, and integration with state-of-the-art research technologies such as high- and super-resolution microscopy, quantitative image analysis, spatial
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Public Health. More information on the College can be found at https://www.uta.edu/academics/schools-colleges/conhi/research . Engineering: All areas of engineering will be considered with an emphasis
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-funded DECIPHER-M consortium (9 partners, €9M), we are building multimodal foundation models that integrate imaging, text, and structured clinical data to predict metastasis risk and identify tumor origin
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partner, POST Luxembourg , one of the country's largest employers and a leading provider of postal, telecom, ICT, and financial services. The successful candidate will join the Computer Vision, Imaging, and
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YOUNG RESEARCHER IN THE FIELD OF EARLY DETECTION OF THE HEALTH STATUS OF PLANTS USING REMOTE SENSING
in processing spatial data, images, or point clouds, an interest in applying artificial intelligence methods in natural science research, an interest in interdisciplinary research work, passion for
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, performing experiments with students and postdocs, analysis of imaging and electrophysiology data, contribution to scientific publications. Please submit your application online at https://apply.ista.ac.at
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Research FieldBiological sciences » BiologyEducation LevelPhD or equivalent Skills/Qualifications PhD in developmental or cell biology Proven experience with multi-step molecular cloning andt) in human iPSCs
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Exploiting activation of senescence tumour suppressor mechanisms by Salmonella enterica for the treatment of cancer School of Biosciences PhD Research Project Self Funded Dr D Humphreys Application
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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