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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Let’s shape the future - University of Antwerp The University of Antwerp is
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in the field of computational political science. Position You will assist in the ongoing research project DEMO-LIES on the link between political representation and political disinformation, funded by
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description → Apply until 16/09/2025 (DD/MM/YYYY) 23:59 (Brussels time
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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computational and machine learning approaches, you will decipher genomic regulatory programs and infer the evolutionary patterns of gene regulatory networks in cortical neurons, study their developmental origin
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advantage. You have (basic) bio-informatics skills or are willing to learn. Prior experience with FLIM (performing experiments, data analysis, e.g. with FLUTE, Flimfit, SPCImage, GSLab, or napari) and/or next
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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