49 assistant-and-professor-and-computer-and-science-and-data Fellowship research jobs at University of Michigan
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one from your current graduate or clinical residency training program. Graduate-level academic transcripts (unofficial is acceptable) Two writing samples, preferably a copy of a previously published
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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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preliminary data for new grant applications. Assist in writing grant proposals, in collaboration with the laboratory director and other senior group members, to obtain funding from federal, private, and
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AI expertise Experience in single-cell and spatial transcriptomics/multiomics data modeling and analysis Computational biology experience Cancer biology analysis experience Modes of Work Positions that
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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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from sociology, anthropology, economics, psychology, information and computer science, statistics, geography, public policy, public health, and medicine, among others. SRC is a unique, world-renowned
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data with behavioral and/or cognitive data in diverse study populations. Required Qualifications* Established record of peer-reviewed scientific publication. Prior experience / comfort with computer
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the project's multiple principal investigators (MPIs), the Post-Doctoral Research Fellow will contribute to the scientific aims of NSAL, including but not limited to: Assisting the MPIs and Project Director on
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. Experience in coding with Python, MATLAB, Julia, C/C++, or a similar program language. Experience with biological data analysis or simulations of dynamics. Knowledge of network science and/or complexity
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communication skills. Experience in coding with Python, MATLAB, Julia, C/C++, or a similar program language. Experience with biological data analysis. Knowledge of network science and/or complexity sciences