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interdisciplinary collaboration, in addition to their own specialty. Skills and knowledge related to data handling, such as the acquisition, analysis, and modeling of observational data, are highly desirable. 2
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acquire advanced expertise in navigation models, spatial representation, object representation, and relational knowledge representation, as well as in planning algorithms based on probabilistic models and
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, antigen presentation and trained immunity) using mouse models that enable CPT1A gain or loss of function. Furthermore, the bioenergetic profile of macrophages both in vitro and ex vivo will be assessed
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-carrier (SC) techniques described in [3], the narrowband beamforming model, where signals received over different antenna elements are identical up to a phase shift, may become invalid so that additional
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for single-cell and spatial omics Deep learning and representation learning to model cellular states and interactions Explainable AI for biomarker discovery and patient stratification Cross-disease modeling
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solve research challenges and model development, as applicable. ● Contribute discrete components of a larger project under the general direction of a senior or principal researcher. ● Prepare complete
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teach undergraduate courses such as: GEOG 141: GIS I: Data Display and Manipulation GEOG 142: GIS II: Data Creation and Project Implementation GEOG 143: GIS III: Spatial Analysis and Modeling or other
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spatial and temporal data analysis using advanced machine learning technologies. The successful candidate will become a part of an interdisciplinary team working to develop machine learning techniques
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. XV produces a very rich 4D dataset (3 spatial dimensions + time), showing lung expansion and contraction, and we are working on understanding the best methods for interpreting this data. The successful
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population changes, and other demographic parameters (survival, fecundity, reproductive success, etc.). These integrated population models (IPMs) are increasingly used in ecology. They offer clear advantages