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the transition. What you will do The postdoc will participate in the interdisciplinary research programme GroenvermogenNL, which supports the large-scale development and implementation of green hydrogen in
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team. · Applies statistical methods to large-scale, longitudinal training-related behavioral data. · Maintains substantial knowledge of state-of-the-art principles and theories
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make a difference in the world! Position Information The Postdoctoral Research Associate is responsible for assisting in the development and application of large-scale modeling frameworks for water and
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with infants/children in LMICs. Experience and competency in the interpretation of neuroimaging data from large-scale datasets. Demonstrated experience building research capacity within LMIC teams
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the Liverpool City Region to build on the Young Voices, Big Ideas project and foster ownership of the Children Growing Up in Liverpool birth cohort study in the wider community, and understand how people perceive
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
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learning to improve detection using multiphase CT imaging and longitudinal biomarker data in routine practice. You will work with multidisciplinary clinical and AI teams on applied research, developing and
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implementation of novel training strategies under experimental constraints, e.g., active learning and other data-efficient approaches Conduct large-scale benchmarking and comparative evaluation of gene
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scientific discovery with a focus on microscopy image analysis. Specifically, we are interested in the development of new methods to identify structures of interest in large datasets (detection, segmentation
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this postdoc position, the focus is on methods and algorithms for large-scale graph analytics, in particular network science approaches for analyzing longitudinal, population-scale relational data derived from