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Spectroscopy and Multi-photon Spectroscopy. Experience in automation software, for example Labview and Matlab. Skills Demonstrable ability to plan and manage independent research.
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developing mathematical algorithms and simulations in MATLAB, in particular with Semidefinite Programming and Sum of Squares and of the analysis and design of feedback control systems using these approaches
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electron microscopy and fatigue testing of metals Skills in in situ testing, FIB sample preparation, and image/data analysis tools (e.g., DigitalMicrograph, ImageJ, Python/Matlab) are beneficial. Strong
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
to program fluently in at least one common scientific programming language such as Python, R, Javascript, or Matlab. Must have experience in sediment transport modeling. Preferred Qualifications, Competencies
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learn new advanced analysis techniques (e.g., in Matlab, R, or Python) if relevant for the task. Write up research results in the form of journal articles. Participate in and co-arrange national and
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of simulation tools (e.g., Multiphysics finite element analysis, Matlab, Labview etc.) cleanroom experience, and characterization of electronic devices are required. Further, knowledge of system level integration
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in systems neuroscience. Ideally you would have experience with mouse behaviour and/or Neuropixels recordings and analysis, as well as with opto/chemogenetics. Being a pro with Python/MatLab helps
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understanding about the electronic properties of semiconductors Understand the principles of optical characterization tools for semiconductors and electronic devices Preferred Qualifications Labview, MATLAB
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for research (e.g. Python, R and RStudio or MATLAB) and using data-driven pipelines with complex bio-behavioural data. Prior knowledge or keen interest in topics at the intersection of experimental psychology
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, and python/Matlab/R or similar languages. Experience with “traditional” climate modelling, data-driven climate modelling, and working with large ensembles of climate/weather model output are advantages