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implemented in the Fortran programming language, and it relies on the platform CUDA for parallelization of the computation over several GPUs’ cores, and has interfaces with Matlab and Python for ease of use
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diverse student body of more than 56,000 and 290,000 Panther alumni. U.S. News and World Report places dozens of FIU programs among the best in the nation, including international business at No. 2
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method, can engineer thousands of defined mutations in parallel in a single test tube in yeast. Strains are tagged by DNA barcodes, allowing to efficiently track mutations in cell populations during
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 6 days ago
Postdoctoral Trainee - Carolina Cancer Nanotechnology Training Program (Postdoctoral Scholar) Vacancy ID PDS004223 Full-time/Part-time Full-Time Temporary Hours per week 40 FTE 1 Work Location Chapel Hill, NC
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of laminar/neuropixel probes and electrical microstimulation to study attention and decision making networks in a behaving animal model together with parallel studies in humans. The project is part of a NIMH
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, calcium imaging, optogenetics and/or behavioural methods. The project is part of a broader research programme designed to use cross-species research to uncover mechanisms for memory in both health and
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permeability selection in variant membrane chemistries. This work will run in parallel to experimental analysis conducted at the University of Exeter using synthetic vesicles to observe permeability
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available in the further tabs (e.g. “Application requirements”). Programme Description The Pre-Doc Award offers postdocs and those interested in a doctorate with a very good degree the opportunity to jointly
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with experience in one of the following directions: Analysis of meta-omics data sets, microbial physiology and cultivation, enzyme biochemistry or activity-based microscopy techniques (e.g. BONCAT
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range of exciting projects: for example, developing machine-learning approaches for the identification of known and unknown metabolites in MS/MS data; meta-analysis of mass spectrometry-based metabolomics