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the Research Council of Norway. In this project, we will use advanced time-lapse imaging, numerical simulations, and reactive mixing theories to better understand and predict the role of fluid mixing as a driver
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imaging (fMRI) data, and the recruitment of research participants for the Fonzo Lab. This position is tied to an R01 project examining the effects of trauma-focused psychotherapy (cognitive processing
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PyTorch, TensorFlow, and Scikit-learn. Familiarity with cloud computing and AI frameworks. Extensive experience working on one or more areas: image processing, machine learning, time series, digital health
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. Familiarity with cloud computing and AI frameworks. Extensive experience working on one or more areas: image processing, machine learning, time series, digital health, bio-signal processing, and wearable
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of the projects. Basic knowledge in coding language, including but not limited to, basics of Linux, MATLAB, Python. Ability to carry out both wet-lab work for sample preparation and dry-lab work for image analysis
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adipogenesis as a paradigm to uncover new molecular pathways by which SUMOylation sustains epigenetic and transcriptional identity during cell differentiation. We expect to contribute to a broader understanding
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including advanced coding in R and/or Python, -An interest and track record in publishing in top academic journals; -Proficiency using GitHub and coding languages, and other modern data management, sharing
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the rewiring of transcriptional programs during initiation of adipogenesis is to be established. This project will utilize adipogenesis as a paradigm to uncover new molecular pathways by which SUMOylation
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techniques, different histological methods and advanced imaging. Contact For further information about the position, please contact Associate professor Anett Kristin Larsen : phone: +47 77 62 52 12 e-mail
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Musculoskeletal and Skin Diseases (NIAMS ) National Institute of Biomedical Imaging and Bioengineering (NIBIB ) Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD ) National