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. Knowledge of performance improvement and evidence-based practice. Basic computer skills. Ability to assess, plan, implement and evaluate patient care, taking into consideration protective interventions
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methods to provide explainable outputs from AI models in presence of attacks on the models or data, and scalable methods that move beyond feature attribution aiming for root cause analysis and decision
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, please visit: https://qbm.genzentrum.lmu.de/application/ Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content
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certification authorities. Knowledge of experimentation and research methodology. Proficiency in quantitative research methods and familiarity with relevant computer programs, such as SPSS, SAS, or STATAl
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(https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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of individual heterogeneity, estimation using machine learning methods and particular challenges present when studying infectious diseases. An overall goal of the project is to improve current practice in
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and up-to-date knowledge of current issues and future directions within the relevant research disciplines as outlined in the Job Purpose which include, but are not limited to, Computer Vision, Deep
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in research field: natural sciences Vacancies/positions: 1 Type of contract: full time Application deadline: 30.04.2026 Estimated date of the contest settlement: June 2026 Envisaged job starting date
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integration, large-scale mobility modeling, and translating advanced systems methods into operational tools used by cities, MPOs, and state DOTs. Position Overview The Postdoctoral Associate will lead and
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sensed estimates; collaborate with the team to develop improved and expanded gridded temperature, humidity, humid heat, and precipitation archives, along with interoperable weather and climate forecasts