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and spatially complex nature of MRI signals. Each MRI examination involves multiple pulse sequences, with signal acquisition being sensitive to coil placement, sensor geometry, B0/B1 inhomogeneities
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transport companies, taxis and other sources of mobility. Development of data-driven predictive models. Analysis of the spatial and temporal variation of transport services and their demand. Analysis
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and spatial omics integration and latent modeling with scVI for batch correction and label transfer Regulatory genomics and motif analysis using tools from MEME Suite or HOMER. Cloud-native NGS workflow
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Professorship of Remote Sensing Applications (https://www.asg.ed.tum.de/rsa), Department of Aerospace and Geodesy, TUM School of Engineering and Design, focusses on methodological research on the analysis and
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dynamics that incorporates the effects of pesticides (from the above experiments) as well as spatial processes such as dispersal and species interactions.4. Bridge data and theory – Test model predictions
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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the production of spatially granular and engineering driven representations of model results. Experience working across disciplines in multi-institution and multi-stakeholder collaborations is desirable
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and robotics, data science, cognitive and brain science and economics and finance. Leveraging its ‘4-in-1’ model of education and residential college system, UM provides all-round undergraduate
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University of Southern California Sol Price School of Public Policy Adjunct Instructor of Urban Planning Department of Urban Planning and Spatial Analysis The USC Sol Price School of Public Policy
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evolutionary mechanisms: for example, heterozygote advantage (HA), negative-frequency dependent selection (NFDS) or spatially/temporally fluctuating selection (FS). Recently, new research showing that balancing