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candidates are expected to be skillful in some, but not necessarily all, of the following areas: experience with software languages and tools such as Python, R, Linux, GitHub, Globus, high-performance
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python and using plant root segmentation software Experience segmenting 3D CT images in plant sciences Experience with high performance computing/high throughput computing resources for research Evidence
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analysis and signal processing Experience working with pediatric/child populations in research settings Familiarity with bilingualism or language/literacy research Experience with MATLAB, Python, or R
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analytics projects as needed (e.g., ticketing, fan engagement, and scheduling). Build and maintain data pipelines and models using R, Python, SQL, and cloud computing resources, following best practices
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analyses and developing habitat maps using marine datasets. Applicants should possess strong analytical skills and experience with spatial modelling and statistical software such as R, Python, or MATLAB
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journals. You have experience setting up quantitative research and can readily program experiments. You have strong statistical skills and can work with scripts, for example in R or Python/Matlab. You have a
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subject. Proven experience with X-ray imaging/diffraction techniques, e.g. XRD-CT, 3D-XRD, µ/nanoCT, STXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability
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related subject. Proven experience with X-ray imaging techniques, e.g. µCT, nanoCT, TXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability to work both
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or Python Experience working in high-performance computing environments Familiarity with version control systems such as Git or GitHub Demonstrated scientific writing and publication experience Interest in
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experimental control and scientific data analysis, preferably using Python, C/C++, MATLAB, LabVIEW or related tools The ability to guide junior researchers and coordinate work across a collaborative experimental