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Field
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establish a multi-scale framework to distinguish genuine neuronal interactions from confounding influences and uncover how precise neuronal coordination relates to large-scale brain dynamics. To this
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will focus on distributed acoustic sensing on pre-existing telecom fiber networks, wavefield analysis, structural and geophysical interpretation, multi-modal data fusion, and lab-scale and field
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, algorithms and statistics. Familiarity with programming techniques for analyzing data sets and experience working with BIG DATA (eg. NGS data in multi-TB scale). Experience using genome alignment software
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, algorithms and statistics. Familiarity with programming techniques for analyzing data sets and experience working with BIG DATA (eg. NGS data in multi-TB scale). Experience using genome alignment
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team of data scientists, software engineers, and experimental researchers on topics including: Developing multi-scale and multi-modal representation learning methods for scientific imaging data (e.g
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in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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Karlsruhe Institute of Technology | Eggenstein-Leopoldshafen, Baden-Württemberg | Germany | about 1 hour ago
development of relevant analytical methods will follow. Establishment of suitable models to explain the results obtained drawing of interdisciplinary and potentially multi-scale approaches will be an
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programming skills and practical experience with leading machine learning frameworks and modern AI environments, including multi- GPU model training and large-scale inference on dozens to hundreds GPUs, are
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skills and practical experience with leading machine learning frameworks and modern AI environments, including multi- GPU model training and large-scale inference on dozens to hundreds GPUs, are
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engineering, interface management, product architecture, or modularization Interest in, or experience with, Model-Based Systems Engineering (MBSE) Understanding of large-scale, multi-domain engineering