50 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof" "UNIS" Fellowship research jobs at University of Michigan
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multiple types of high-dimensional data. Researching and implementing novel algorithms for analysis of latent factors and their dynamics. Conducting literature searches, manuscript preparation, and
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mentor graduate students, contribute to grant proposal development, engage in agency outreach and partnership activities, publish high-quality research articles, and represent U-M at national professional
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. Responsibilities* Design, implement, and evaluate LiDAR-based experiments in lab and real-world settings. Develop and test algorithms for object detection, tracking, and classification using LiDAR sensors. Help
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Medicine and Bioinformatics. The specific objectives of the project are to (i) deploy network analysis methods to genomic data (50%), and (ii) develop such algorithms including community detection algorithms
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. Job Summary Weil Institute Postdoctoral Data Scientist Role Description The Weil Institute is in search of a Postdoctoral Fellow to develop predictive analytics that will help improve the treatment
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model systems and functional studies to understand this process. Our goal is to develop new, targeted treatment strategies for men with advanced prostate cancer. The position is in a collaborative
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knowledge graphs to develop and test new measures of innovative potential. The project will also assess how these measures relate to multiple indicators of research impact in biomedical research, with a
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, operation of the scanner, data acquisition and analysis, image evaluation, and statistical analysis. The fellow will also be expected to prepare manuscripts and conference abstracts related to projects and
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public research institution, Michigan Engineering's mission is to provide scientific and technological leadership to the people of the world, develop intellectually curious and socially conscious minds
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methodology development as well as applied cancer bioinformatics in a variety of disease sites, including the incorporation of statistical, machine learning & QML ideas. Multiple collaborative opportunities