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available datasets. Utilize advanced statistical and analytical tools (Python, R, SQL) to derive actionable insights from data. Lab activity support Participate actively in team meetings, brainstorming
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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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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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of extracted experimental parameters Design and execute Python-based scripts to infer derived parameters and standardize units and formats Integrate external databases and online resources to enrich curated
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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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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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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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and perform simulations using established software like MEEP and COMSOL, as well as custom-written code based on languages like C++, Python, Matlab Lead papers and publish in high-impact journals
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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