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- Computer Vision Center
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Field
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cancer metabolism, with particular expertise in the study of tumor metabolism, as well as proven experience in the establishment, culture, maintenance, and characterization of tumor organoid models and
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on endocrine and neuroendocrine tumours, integrating preclinical models, molecular profiling and translational approaches to identify novel therapeutic vulnerabilities and biomarkers associated with treatment
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. The QML-CVC team (https://qml.cvc.uab.es/ ) is part of the Computer Vision Center at the Universitat Autònoma de Barcelona; the CVC is a center with over 150 persons working machine learning and computer
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studies in mouse models of disease. This role offers a defined period of advanced, mentored training, providing the opportunity to deepen expertise, contribute to high-quality research projects, and
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vitro biofilm models of clinically relevant, antibiotic-resistant bacteria. Quantify the bactericidal activity of a library of PSC compositions against planktonic and biofilm-grown bacteria, using time
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applied research using plant experimental model systems, crops and farm animals) make extensive use of genomic technologies and large sets of genetic and genomic data (https://www.cragenomica.es/sites
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cell culture models. Experience with in vivo imaging. Competencies and Skills: We value not only technical expertise but also the demonstration of core competencies such as Communication, Teamwork and
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performance through iterative design-test-feedback cycles. Participate in the design and simulation of photonic devices and integrated circuits using state-of-the-art modeling tools. Support the development
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models, stochastic processes on networks and graphs, network communication processes, and reports. The fellow will work with the other SUPPORT fellows to develop statistical methods and data resources
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function of these cells, we combine directed differentiation of human pluripotent stem cells, in vitro and in vivo models of human normal and leukemic development, and state-of-the-art epigenomic and