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Field
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for ML / LLM algorithms working over free-text clinical data and potentially mixed modalities (waveform, DICOM images etc.) Data manipulation and analysis capability, e.g. machine/deep learning in R/Python
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programming tools (e.g., LabVIEW, Python, MATLAB) ENED 1120 - Foundations of Engineering Design Thinking II (a design centered course that builds foundational knowledge of multiple programming tools (e.g
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platform and coordinating the integration and testing of commercial cellular equipment. The candidate must have fluency in multiple programming languages such as bash scripting, C++ and Python and comfort
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. Experience with next-generation sequencing and/or exome/whole genome sequence analysis. Computer programming (e.g. R/Python) and bioinformatics experience. Familiarity with NGS clinical testing, databases
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learning techniques Develop and implement complex analyses pipelines, programming, and data visualization techniques Creatively and effectively integrate data from multiple sources to accelerate discoveries
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(e.g., Vue, React), Python Knowledge, Skills, & Abilities ABILITIES Able to develop software that meets technical specifications to satisfy business requirements Able to write code that utilizes basic
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one statistical software (e.g., R, Stata, SPSS, Python) Expertise in quantitative analysis, with preferred skills in Quasi-experimental evaluation techniques (e.g., Difference-in-difference, PSM) Social
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electronic health records (EHRs) from multiple UK hospital centres using advanced data analytics including machine learning, deep learning, and statistical techniques—with a particular emphasis on deep
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Microsoft, open-source, and web standard technologies such as Python Flask, .NET Web Forms, .NET MVC, C#, CSS, HTML, ReactJS, jQuery, and T-SQL to design, develop, and deploy web-based applications
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health data, c. QA/QC of collected and analyzed data and data validation and verification against independent sources, d. data summary and analyses, e. modeling of individual or multiple elements