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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with
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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with
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conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a related field together with strong programming skills in Python, R
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. Software and programming experience may include: R, STATA, Esri Arcmap, python, Leaflet, PostgreSQL, CSS, JavaScript, JQuery, Bootstrap, PHP, QGIS, PostGIS, Mapserver, Tableau, Openlayers, Geoserver, R Shiny
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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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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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coding environments (e.g., R, Python). Ability to work collaboratively with a team of diverse backgrounds. Excellent written and verbal communication skills. Experience in processing large data sets
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major programming language, such as Java, C/C++/C#, Python, and preferably in several languages; proficiency in the Linux operating system and deployment and configuration of virtualised environments
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Engineering, Mathematics, Statistics, or related fields. • Strong programming skills in Python, Java, C++, etc. • A solid foundation in generative AI, machine learning, and related areas. • An Interest in eye
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publications in peer-reviewed journals, demonstrating a commitment to scientific excellence and innovation. Experience with data analysis pipelines, programming (e.g., Python, R), and bioinformatics software