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on the subcellular spatial and temporal dynamics of these interactions, with an effort to resolve how different pharmacological approaches may strategically and uniquely alter them. The position is limited to a period
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 3 months ago
combines expertise in advanced techniques of demographic, longitudinal and spatial analysis. The student is expected to use the opportunity of preparing a PhD thesis as a collection of research articles
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., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis, machine learning, deep learning
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requirements are Experience in working with large-scale spatial-temporal traffic and/or travel behavior data, e.g., loop detector, floating car data, GPS data, cellphone data. Experience with transport
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imaging with image analysis, and spatial genomics and proteomics. The position will be responsible for participation in seminars, professional development opportunities, manuscript preparation and
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framework exploiting the use of physical and geometrical conservation laws in a variety of spatial discretisation schemes (i.e. Finite Element, Finite Volume, Meshless). The resulting conservation-type
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to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures of health, well-being, and human
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architectures [5] and Neural ODEs [2], creating a cohesive end-to-end hydrological model. Transformers will be utilized to pre-process and analyse the raw input data, capturing essential spatial and temporal
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, or spatial relationships of objects—and to indicate when it is unsure about its input. Key expected outcomes include the creation of monitoring algorithms that identify early signs of performance issues, and
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to the collected dataset. Deep learning will focus on physics-based features developed earlier. Convolutional layers will be used to extract spatial patterns, while LSTM layers will capture temporal aspects across