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, calibration, reproducibility) Implementing and maintaining Python-based data processing and analysis pipelines Quantitative interpretation of nanoscale microstructure data in deformation–precipitation
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analysis using Python. Organized and methodical in data collection and lab management. Ability to work alone or with others. Reliable and committed to the lab. Previous experience as a lab manager. Previous
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spatial statistics or clustering analyses (e.g., fuzzy k‑means) Ideal candidates will have experience with: ArcGIS Pro, QGIS, or Google Earth Engine Python (rasterio, geopandas, numpy), R, or similar Remote
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and experience equal to ten years. Knowledge, Skills & Abilities : 2+ years of experience developing AI applications in production environments Proficiency in Python LLM/RAG related libraries
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degree qualification: Graduate in Geology or equivalent Specific Requirements Professional with proven ability to handle geological data processing software (Stereo32, QGis) and Python programming, as
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include cloud based Trusted Research Environments (TREs.), Microsoft Azure, SQL, Python and Git. You will be based within the Faculty of Health and Life Sciences, reporting to the CHIL CTO, and will work
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allow you to develop competences in Analysis of population recordings (suite2p and python) Quantification of behavioural (DeepLabCut and python) Analysis of the MICrONS dataset ESSENTIAL REQUIREMENTS
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of software and resource sharing in collaborative work. DATA EXTRACTION, PROCESSING, AND ANALYTICS This position will utilize data science and statistical software such as Python, R, and SAS, to analyze and
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with statistical computation (e.g., R, Stata, or Python) and data management. PREFERRED: Bachelor's degree in social science, statistics, computer science, or a related field; familiarity with social
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issues. Proficiency in urban modeling tools such as MATLAB, Python (especially libraries like Pandas, NumPy, SciPy, GeoPandas, etc.), and R. Advanced skills in predictive modeling and machine learning