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Brandenburgische Technische Universität Cottbus | Cottbus, Brandenburg | Germany | about 2 months ago
Learning commencing on April 1st, 2027. The Junior Professorship in "Probabilistic Methods in Machine Learning" is at the interface of applied mathematics, statistics, and computer science. It is dedicated
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spanning artificial intelligence, circuit design, computer architecture, and embedded systems engineering. Where to apply Website https://www.academictransfer.com/en/jobs/362502/phd-on-emulation-framework
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modern machine-learning techniques, will be exploited to improve the discrimination between the different polarization states. The analysis will use the complete Run 2 and Run 3 datasets collected by
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manuscript and technical papers and assistance with grant proposal development in coordination with CCU CubeSat program faculty. This position may also teach an engineering course per semester in
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of related peer-reviewed manuscript and technical papers and assistance with grant proposal development in coordination with CCU CubeSat program faculty. This position may also teach an engineering course per
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postdoctoral appointment in Remote Sensing of the land surface, with a strong interest in the integration of geospatial Artificial Intelligence (AI) and machine learning. Are you enthusiastic about the chance to
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 2 months ago
analysis, machine learning, eye tracking). The main duty of the post-holder will be statistical consulting. A broad knowledge of statistics in this scientific area is required. The applicant should have in
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for a PhD project focused on advancing the design and functionality of deployable structures through the integration of 4D printing, architected materials, and scientific machine learning (sciML). A part
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Pastrana, Guillermo Suarez-Tangil. IoC Stalker: Early Detection of Indicators of Compromise. Annual Computer Security Applications Conference (ACSAC). December 9–13, 2024. (link: https://suarez
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acquired across multiple anatomical regions to form a patient-level assessment. This PhD project will investigate novel deep learning methodologies that jointly model anatomical structure and prediction