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work environment. Experience in and understanding of the challenges facing higher education organisations Experience in Python A self-starting attitude Serverless computing with AWS is key to our
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reports to publication. Researching new software solutions, such as R-packages, Python, Google colab, Jupyter notebook, ShinyApp, SAS PROCs or macros that might be useful to Statistical and Data Analytics
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recruitment, screening, consent, scheduling, regulatory compliance (GCP/IRB/FDA), and study documentation. Data management, preprocess/analyze large-scale neural data using Python/MATLAB; contribute
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to interpret data trends Proficiency in Microsoft Excel or Google Sheets (e.g., sorting, formulas, basic visualization) Familiarity with data analysis tools (R, SPSS, Python, or similar) Ability to synthesize
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-performance computing, and Python-based data analysis. Equivalent combination of education/experience. Equivalent education and/or experience may substitute for minimum qualifications except when
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Qualifications Experience with physical oceanography, coastal systems, or offshore wind research Proficiency in scientific programming (e.g., Python, MATLAB, or similar tools) Strong communication skills
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tools, data science/statistical techniques, ML techniques including (but not limited to): Data analysis programming and visualization languages (R, Python, SAS); Applied statistics including MVA, MLR
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or Python. Responsibilities include teaching two undergraduate courses in each of Lawrence’s three ten-week terms. The successful candidate will be the third statistics and data science faculty member in
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Python for code development and ML model training and inference, demonstrate excellent communication skills and be fluent in English, show strong interpersonal skills and the ability to work in an
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analysis Experience working with R and Python for data analysis and image processing Familiarity with image analysis tools (e.g., ImageJ/Fiji, CellProfiler, or similar platforms) is desirable Education and