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project supported by funds from the Economic and Social Research Council (ESRC). The project aims to examine emotion processing and emotion regulation in people with convictions for sexual and violent
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proposal development and preparation of high-quality publications in top computer security, privacy, embedded systems, sensing, and networking venues. ● Pursue research topics such as protecting
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on advanced technologies including semantic/task-oriented data processing, signal processing, network resource management to improve the performance of the future wireless communication systems. Finally, due
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. This document will provide information of what criteria will be assessed at each stage of the recruitment process. * Please note that this is a PhD level role but candidates who have submitted their thesis and
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the internal application process. Welcome to The Ohio State University's career site. We invite you to apply to positions of interest. In order to ensure your application is complete, you must complete
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Limitation:Temporary (2 years) Contract:TV-L Your tasks Develop and implement computational pipelines for processing and analyzing ONT RNA/cDNA sequencing data. Apply machine learning and signal processing approaches
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GESIS - Leibniz Institut für Sozialwissenschaften | Mannheim, Baden W rttemberg | Germany | about 8 hours ago
, involving software developers, language experts and language service providers. Your tasks will be: Managing the project from a content point of view, in close collaboration with a GESIS internal software
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to employment preference must clearly indicate so in their application and submit all relevant supporting documents. The Faculty reserves the right to conduct interviews and professional testing for candidates
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knowledge in arithmetic, algebraic or complex dynamics. Informal enquiries can be made by contacting Holly Krieger at hk439@cam.ac.uk . If you have any queries about the application process, please email
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Project The Adaptive Design for AI-Driven Processes in Transforming Dynamic Landscapes (ADAPT) project develops scalable, data-driven design methodologies that transform dynamic environmental processes