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manipulations. Assay Development: Support the development of cellular and biochemical assays to complement in vivo findings. Data Analysis & Interpretation: Analyze complex datasets from in vivo and in vitro
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) microscopy, FLIM, STED, lattice lightsheet microscopy, fluorescence correlation spectroscopy (FCS), image processing and analysis and spectral imaging. More information about the ABIF can be found at: http
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The University of North Carolina at Greensboro | Greensboro, North Carolina | United States | 15 days ago
will perform grant-funded research projects, including experimental design, sample preparation, data acquisition, data analysis and interpretation, research presentation at national/international
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research management and other data analysis software. Application Materials Apply online at https://hr.missouri.edu/job-openings , Job ID 58392. Please submit a single PDF file that includes 1) a cover
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corpus in accordance with ethical principles and using appropriate tools (e.g., API) discourse annotation and analysis concerning selected ethnic groups via computer-based methods the use of embedding
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to complement in vivo findings. Data Analysis & Interpretation: Analyze complex datasets from in vivo and in vitro experiments; present findings to cross-functional teams and industrial biotech. partners
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employment is 2 years. You can read more about career paths at DTU here . Further information Further information may be obtained from Andrey Rivkin, DTU Compute, https://orbit.dtu.dk/en/persons/andrey-rivkin
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scientific publication and writing articles in international journals; 8) Experience in data visualization tools and advanced statistical analysis (e.g., pandas, scikit-learn, matplotlib, seaborn, SHAP
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Post-doctoral Fellow in the Department of Orthopaedics and Traumatology, School of Clinical Medicine
cell (iPSC) technology to create disease-in-a-dish models for high-throughput screening. Perform sophisticated transcriptomic data analysis (e.g., RNA-seq, single-cell RNA-seq) to identify novel
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research with a strong emphasis on digital health, particularly the innovative application of wearable sensor data analysis and mobile health (mHealth) application development. The goal of this research is