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Maintain detailed records of results and prepares written reports acceptable to the Principal Investigator and funding agencies Other duties as assigned Unit URL https://uiexperimentalforest.org/ Position
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well as pediatric malignancy. The successful candidate will have experience analyzing data, and proficiency in standard statistical software, including SPSS as well as R. Knowledge of python is a plus. If the
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combination of education and experience Skills Required: Strong proficiency in one or more modern programming languages (e.g., JavaScript/TypeScript, Java, C#, Python) Solid understanding of web‑based
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applied statistics, data science, machine learning, text analysis, and familiarity with coding in R and/or Python. All applications must be submitted through Columbia University?s Academic Search and
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quality assurance Furthermore, collaboration with experimental and other theoretical groups in Vienna is desirable. Candidates should also actively contribute to and collaborate with the CRC TACO, https
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contributor in technology governance and long-term IT strategy. The full job description is available, here: https://www.dropbox.com/scl/fi/wsfq3tkylrvbj54db5aoi/Principal-SW-Engr-Final-updated-12-19-25.docx
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to institutional workflows by leveraging expertise in Python, Azure AI Foundry, and machine learning to build scalable, user-centric AI applications. The developer collaborates with cross-functional teams
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, machine learning and computer vision techniques, statistical data analysis, and Python programming. Activities will include field calibration and validation of models and data integration into a decision
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their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? The position is in the NMR facility within LIST’s Elemental
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programs. Expertise in a range of engineering-related tools and applications, to include MatLab/Python, EnergyPlus, Labview, Excel, including libraries for conducting numerical analysis of time series data