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% - Ultrasound Data Collection and Data Analysis 30%-Conference Abstract and Manuscript Preparation Required Qualifications* PhD in Mechanical Engineering, Electrical Engineering, Computer Science, or related
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such as transformers, state-space models, and diffusion models will also have experience on single-cell and spatial transcriptomics and multi-omics data modeling and analysis. Mission Statement Michigan
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recruiting a post-doctoral researcher to develop computational models to study the spatial organization and microenvironment interactions in tumors using spatial multiomic data. The lab focuses on mathematical
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the position and outline skills and experience that directly relate to this position. Please also include the names and contact information for three references. Preference may be given to applications received
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to the postdoctoral candidate. Participate and lead all aspects of the clinical trial research, including subject recruitment, scheduling, data collection, processing, and data dissemination. Ensure that all
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Medicine and Bioinformatics. The specific objectives of the project are to (i) develop mathematical and data analysis methods to analyze resilience, robustness, and tipping points of network dynamics, when
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stakeholders to design oligo modifications aligned with project goals. Support experimental design and data analysis to ensure robust technical outcomes. Resource Management & Compliance Maintain inventory
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with diverse experiences to apply. Please visit: https://medicine.umich.edu/dept/michigan-neuroscience-institute for more information about the Institute. Why Join Michigan Medicine? Michigan Medicine
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interventions for preventing overdose, data modeling, national surveys, policy research, epidemiological research, and health services research on pain, addiction, and overdose. Expectations Selection will be
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Research Fellow. CID is a multidisciplinary research center that carries out cutting-edge substantive and methodological research on social and economic inequality and helps expand the scientific data