15 parallel-programming-"Multiple"-"Simons-Foundation" Postdoctoral research jobs at University of Miami
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, coatings, and microneedles. Multiple physical, chemical, and mechanical characterization techniques such as SEM, FTIR, NMR, rheology, and nanoindentation will be used to evaluate the properties of our
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: bioinformatics, computational biology, data science, biostatistics • Working proficiency in appropriate programming languages and software (eg. R, Python) • Excellent oral and written English
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fundamental mechanisms of gene regulation, and transcriptional circuits including gene-regulatory networks, feedback regulation, and regulation of stochastic expression noise in multiple model systems ranging
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) are fully benefited employees with UM health insurance/dental/vision, life insurance, retirement program, etc. Applicants from groups that are traditionally underrepresented in the STEM are strongly
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priorities, and recommends schedules. 2. Presents research findings at local and national scientific conferences. 3. Writes technical publications and reports. 4. Designs and writes programs to perform
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priorities, and recommends schedules. 2. Presents research findings at local and national scientific conferences. 3. Writes technical publications and reports. 4. Designs and writes programs to perform
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programs to perform analysis and produces written reports on results. Collects pilot data to help support new and competing renewal applications. Supervises undergraduate and graduate research students and
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mechanics, FEA, CFD, or equivalent field. Proficiency in one or multiple finite element analysis software (e.g., ABAQUS, LS-Dyna, ANSYS), and in computational fluid dynamic software (e.g., Fluent, CFX
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such as glaucoma, macular degeneration, and uveitis. Programming in Python and R languages with knowledge of Google Tensorflow, PyTorch, scikit-learn, and Keras or other related deep learning libraries
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such as glaucoma, macular degeneration, and uveitis. Programming in Python and R languages with knowledge of Google Tensorflow, PyTorch, scikit-learn, and Keras or other related deep learning libraries