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further develop quantitative spatial analysis methods and Python-based workflows using the MuSpAn (Multiscale Spatial Analysis) framework, extend analyses to additional patient cohorts, and prepare findings
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for engineering problems, comfortable with Python and Matlab Required duties: Preprocessing of climate data from global and regional climate models, relevant for the engineering case studies that will be included
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undergraduate student with Python experience to join Dr. Maya-Lastra’s research lab on a project in automated lexicon enrichment for botanical data. The successful candidate will help develop a bootstrap pipeline
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Analyst 3 will use R and/or Python to develop reproducible data processing workflows, automate data extraction and transformation, interface with REDCap APIs, conduct data quality assessments, prepare
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for Immuno-Oncology and the Cancer Research UK Oxford Centre. They will apply and further develop quantitative spatial analysis methods and Python-based workflows using the MuSpAn (Multiscale Spatial Analysis
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models, including fine-tuning, prompting, evaluation, or retrieval-augmented generation. ● Strong programming skills in Python with experience in deep learning frameworks such as PyTorch
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so one lab's deposit is usable by another. Model interfaces — modular Python APIs that let representation models, tokenizers, and downstream models be swapped and composed without rewriting
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Python environment of spectral libraries, chemometric procedures for processing drone-acquired hyperspectral data, and classification and model-selection algorithms aimed at identifying asbestos-containing
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. AstroFetch uses large language models to translate natural-language questions into archive queries, data analysis, and visualizations. A public beta version already exists, built in Python and supporting
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teaching the fundamentals of programming, including object-oriented programming, data structures and Python. Additional teaching expertise in web development would be an advantage, as would wider teaching