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between various imaging modalities and multi-omics during aging and development. • Implementing computationally intensive algorithms on high-performance computational clusters
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JOB SUMMARY The Physiological Acoustics Lab (http://escabilab.uconn.edu) at the University of Connecticut seeks applicants for a postdoctoral position in systems and computational neuroscience
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 5 hours ago
secure power. For more information about ARPA-E visit https://arpa-e.energy.gov/. Stipends The DOE Scholars Program provides stipends starting at $1,000 per week for graduate students and recent graduates
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to apply; however, the greatest interest is for applicants with interest in one or more of the following topics: complex dynamics, computability in dynamical systems, smooth ergodic theory, symbolic dynamics
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scientific programming (Python, MATLAB, C/Fortran, or equivalent) and high-performance computing workflows. Proven ability to work across disciplines and manage complex modeling tasks. Excellent written and
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, lipid vesicles, polymer physics, active materials, single molecule biophysics, biomaterials, materials chemistry, fluid mechanics, rheology, and computational modeling. Candidates should apply at https
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multiparameter immunophenotyping, transcriptomics, proteomics, leukocyte functional assays, and statistical and computational biology to define mechanisms of cellular and humoral immunity to the transplanted organ
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. The appointment will be housed in the Division of Life Sciences; courtesy cross-appointments with other units on campus may be possible. The chosen candidate will be expected to undertake a programme of research
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for generations to come. To learn more about SEAS and our values, please visit our website at https://seas.umich.edu/about/seas-values. Why Work at Michigan? In addition to a career filled with purpose and
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI