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Field
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for implementing the model as a computer simulation and analysing it within a health-economics framework using standard computational techniques. The post-holder will also be responsible for writing up the findings
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to work within a team environment. Adaptability to a fast-paced, dynamic environment. Multitasking essential. To learn more and apply, please visit: https://careers.dana-farber.org
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robust professional development opportunities, and a competitive benefits package designed to support your career and well-being. Learn about NREL’s critical objectives: NREL's Mission and Vision . Job
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developing ideas for application of research outcomes. This post also be linked to research activities linked to the Faculty’s research platforms such as the Power Electronics, Machines and Control Research
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journals (including as the main author), such as ICSE, FSE, ASE, ISSTA, SANER, ICPC, ICSME, MSR, TOSEM, JSS, I&ST, TSE, and EMSE • Experience publishing in related fields, such as data mining and machine
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interested in applicants who use advanced quantitative methods, including computational modeling, machine learning, and/or analyzing structural and functional neuroimaging data. Specific activities may include
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computer skills for accurate data collection using various hospital EMR systems (primarily EPIC systems) and willingness to learn various Data Capture systems (WebDCU, RAVE, Red-Cap) ability to work on site
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presents an exceptional opportunity for a suitably qualified and motivated individual to engage in applied research at the intersection of artificial intelligence , process monitoring , machine learning
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research, oncology microbiomes, or environmental resistome surveillance. Familiarity with spatial metagenomics, single-cell microbiome analysis, or multi-omics data integration. Knowledge of machine learning
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of complex and challenging patients in critical care. The curriculum is composed of multi-modal learning opportunities that may include the following: in-person didactics, online classrooms, simulation