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Purdue University, Department of Physics & Astronomy Position ID: Purdue -Department of Physics & Astronomy -POSTDOC [#30326, 38314] Position Title: Position Type: Postdoctoral Position Location
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emerging types of national emergencies and evaluate their spatial and operational implications. This will include an analysis of UK population distributions, terrain, infrastructure access, and airspace
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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
-microscopy, proteomics and metabolomics. This project will study large protein secretion systems, drug-efflux pumps and lipid transport towers to provide means to integrate spatial information and metabolic
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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 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
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spatial omics datasets. The position will also contribute to multi-modal data integration efforts that combine imaging, genomics, and machine learning approaches. Key Responsibilities Data Processing
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multiplex immunofluorescence and spatial transcriptomics, with a special focus on various types of nerves and nerve fibers in the tumor microenvironment Analysis of relevant circulating proteins using
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
on sustainable feedstocks. Supervise and mentor PhD students and postdocs. Drive national and international research funding applications. Collaborate with academic and industrial partners, including engagement
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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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-scale job ads datasets, spatial datasets, patents). Conduct data analysis using econometric and statistical tools. Excellent knowledge of R is expected. Good knowledge of Python, experience with modern