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Field
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fellow salary, which is determined by the number of years post PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard
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areas such as statistical modeling, machine learning, intensive longitudinal data analysis, micro-randomized trial design, natural language processing, Al applications in digital health, and real-world
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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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( 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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Future robots must perceive, predict, communicate, and decide reliably in complex, human–robot shared environments. The Mobile Robotics ( https://www.aalto.fi/en/department-of-electrical-engineering
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materials that underpin device operation (see https://doi.org/10.1016/j.joule.2023.03.002 for a recent example of this approach from the group). This project will be carried out in collaboration with the
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machine-learning methods to identify and quantify species interactions from acoustic recordings. Construct ecological interaction networks from the inferred acoustic data. Contribute actively to scientific
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defects Analysis and interpretation of experimental data Documentation and publication of results in reports, scientific manuscripts, and conference presentations in English Collaboration with and co
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optimisation, reinforcement learning or uncertainty analysis is advantageous Experience in processing and analysing time-series data A structured, independent and solution-oriented approach to
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Primary supervisor David Dowe Co-supervisors Nenad Macesic Research area Data Science and Artificial Intelligence Antimicrobial resistance (AMR) is one of the most significant and immediate threats