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. The research in the PhD project will focus on core spatio-temporal machine learning method development, including: generative models for grid-based and particle-based spatio-temporal data; controlled generation
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challenging conditions (see https://tissueresilience.com ). Harnessing powerful in vivo models, our work spans multiple biological scales - linking the molecular cell biology of individual cells to the health
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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Mathematics and Statistics we conduct research within the theory and implementation of biomathematics, biostatistics, spatial modeling, differential equations, Bayesian inference, large-scale computational
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, or glaciology. We invite applicants to highlight experience with spatial analysis tools, such as GIS, or other quantitative approaches, which could include modeling or AI. The teaching load is three courses per
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of large spatial and temporal biodiversity datasets. Since almost 20 years the Rhine-Main-Observatory (RMO; https://www.senckenberg.de/rmo/ ) has been part of the German LTER network (https://www.ufz.de/lter
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at various spatial and temporal scales, ranging from individual cells to tissues, organs, and full physiological systems. Computational modeling and simulation: development of constitutive laws, finite-element
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on expectations elicited via tailored household and firm surveys (carried out by another team member) and other spatial and physical climate risk data. The goal of this agent-based modeling is to identify
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more information about this assessment on our website about knowledge … Where to apply Website https://www.academictransfer.com/en/jobs/357324/phd-position-on-predictive-mode… Requirements Additional
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ACCE+ DLA programme: Landscape-scale drivers and limits of endangered species spatial and temporal distribution School of Biosciences PhD Research Project Competition Funded Students Worldwide Prof