53 assistant-and-professor-and-computer-and-science-and-data Fellowship positions at University of Michigan
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, and ethical standards in research conduct and data handling. Required Qualifications* Ph.D. in Electrical Engineering, Power Electronics, or a closely related field, with a strong background in power
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Qualifications* PhD Degree in Engineering, Computer Science, Data Science, Applied Mathematics, Statistics, or a related field Familiarity with (biomedical) signal processing Experience working with clinical data
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environment. Successful candidates will be able to use electrophysiology, neuroimaging, chromatin biochemistry, functional genomics/informatics, and human 2D and 3D neuron models to explore the roles
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goals of establishing their own independent research program. Responsibilities* Plan, coordinate, execute, and disseminate basic-science research focused on tendon, bone, and muscle development and
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subjects. The candidate will work under direct supervision of the Principal Investigator Dr. Abhijit Parolia an Assistant Professor in Pathology & Urology in the Michigan medical school. The candidate will
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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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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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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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specific drugs and pharmaceuticals. Help maintain lab organization and record all information in an official laboratory notebook. Maintain organization of lab protocols, equipment operation, and standard
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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