34 parallel-and-distributed-computing Fellowship positions at University of Michigan in United States
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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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bundle platform we developed to increase rigor of structure-function quantifications. We also perform CRISPRa high throughput screening and massively parallel reporter assays (MPRAs) in iPSC-CMs. A current
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that machine learning applications are developed with ethical considerations in mind. Participate in regular meetings with the research group. Required Qualifications* Ph.D. in Electrical Engineering, Computer
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with Owen-Smith and other members of the IRIS team. Familiarity and demonstrated expertise with network and computational science methods, science of science research, creation and manipulation of large
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) Applications are due on November 18, 2025. If you have questions about how to apply, please contact Taubman College HR at taubmancollegehr@umich.edu. Job Summary The Architecture Program at the University
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analysis. Required Qualifications* A PhD in hydrology, water resources engineering, environmental science, civil engineering, atmospheric sciences, computer science, or a related field is required either
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Apply Now How to Apply Applicants must submit TWO separate applications: one to the President's Postdoctoral Fellowship Program (PPFP) site (http://presidentspostdoc.umich.edu/ppfp-application.php
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that will define the CNRE. CNRE research is both computational and experimental; we work on exciting problems in diverse areas such as bio-fluid interactions, signatures, wave energy, advanced materials
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to facilitate a multifaceted Digital Scholarship Fellows program. This program, which will comprise student, faculty, and community fellows, will offer a way for the Digital Scholarship program to meet existing
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for improved interpretability and generalization. Familiarity with high-performance computing (HPC), cloud platforms, or GPU clusters. Demonstrated ability to work collaboratively in interdisciplinary and cross