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Job description The job involves formal semantic and pragmatic modeling of Information Structure-related phenomena from a diachronic perspective. Information Structure-related phenomena are to be
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. Applications will be accepted until the position is filled. Job profile The successful candidate will train recurrent neural networks to learn the generative structure of existing behavioral, EEG and MEG data
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, and brain computer interface tasks. This project will support our goal of testing the Controllosphere Theory of cognitive effort (see doi 10.1037/rev0000467). A Ph.D. and background in computational
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profile of your interests and show you relevant ads on other sites. They do not store personal information directly, but are based on the unique identification of your browser and device. If you do not
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international mobility You have a solid foundation in electrophysiology and neurophysiological data analysis utilizing Python or MATLAB software. Experienced with electrophysiological recording using multi
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experience with FLIM (performing experiments, data analysis, e.g. with FLUTE, Flimfit, SPCImage, or napari) and/or next generation sequencing data-analysis and ability to code are considered an advantage. You