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. • Strong proficiency in Python, FastAPI, and PostgreSQL. • Hands-on experience with LLMs, vector databases (e.g., Pinecone), and NLP tools. • Familiarity with clinical trial data structures, academic
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high-dimensional biological datasets, including next-generation sequencing data. • Proficiency in R and/or Python for computational biology and bioinformatics analyses. • Strong background in statistical
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analyzing genomic, transcriptomic, proteomic, spatial multi-omics, imaging, or other high-dimensional biological datasets. · Proficiency in R and/or Python for computational biology and bioinformatics
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. • Proficiency in R and/or Python for computational biology and bioinformatics analyses. • Strong background in statistical analysis, data integration, and scientific data visualization. • Experience developing
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, imaging, or other high-dimensional biological datasets. · Proficiency in R and/or Python for computational biology and bioinformatics analyses. · Excellent analytical, organizational, written, and verbal
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epidemiology and biostatistics. Advanced knowledge of R, Python, SAS or other coding language for data management and epidemiologic analyses. Advanced experience linking and working with provincial
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computer software packages (e.g. Microsoft Office) for lab documentation, data entry and analysis. Proficiency in computational analyses, including running tools on the command line, python programming, R
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programming capabilities (1-3 years minimum experience) in languages relevant to accelerated materials discovery, particularly Python Behavioural competencies Research - Communication (Level 3) Research
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/embedded systems Integrating hardware with software Use of collaborative development tools such as Git Programming for FPGA and/or microcontrollers (C/C++) Programming application software in Python
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) in languages relevant to accelerated materials discovery, particularly Python Behavioural competencies Research - Communication (Level 3) Research - Creative thinking (Level 3) Research - Teamwork