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your professional network. You will also have opportunities to present your work at leading conferences, engage in international collaborations, and develop a strong professional profile in computational
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topics in their nation of residence. Professor Seaborn is lead of and a listed supporter on the IDE+A Network: https://the-idea.network Click the 'Apply' button below to register an account with our
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inductive biases, we aim to identify key mechanisms that drive rapid learning in the visual system. The goal is to create a robust mechanistic neural network model of the visual system that not only mimics
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environment at the University of Kassel. Its offers are open to all academics and artists in the qualification phase at the University of Kassel. Further training / transferable skills Kassel Graduate Programme
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 10 days ago
Assistant position, with the successful candidate embarking on a PhD programme at LSHTM. It is anticipated that the role will lead to a further 18 month funded opportunity at Max Planck Institute
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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading
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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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will generate unprecedented volumes of data, to be processed at a central facility, and distributed to a global network of SKA Regional Centres (SRCs) for storage, access, and scientific exploration
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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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computational modelling to be used to design and re-engineer flower architecture. The RA's main focus will be on computational modelling of gene regulatory networks for predicting the mechanisms leading