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positions may start their PhD projects at other times throughout the year. The average duration of PhD research in the IMPRS is between three and four years. Application deadline A central application call
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research questions from several fields such as software and domain engineering, system modelling and analysis, application adaptability and integration, human computer interaction, security, and
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of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do The complete design and implementation of analog circuits including
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Neuroscience uses theoretical approaches from this broad range of disciplines to integrate experiment, data analysis and modelling in order to understand the brain. Furthermore, it makes a scientific language
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of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do Design innovative memory arrays for non-volatile memories Develop
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of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do Responsible for RTL design (VHDL, Verilog) of digital blocks and
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of embedded machine learning, neuromorphic hardware and deep learning accelerators. Want to get more information? Click here. What you will do Responsible for writing Verilog/ VHDL code for AI blocks Perform
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of the a.r.t.e.s. Graduate School provides a structured doctoral model with an interdisciplinary approach. The individual doctoral studies are combined with a set of guided courses. Supervision is provided through a
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regulation, using various models of developmental and disease biology. The past three decades of genetics research have been catalysed by technologies that map genomic information at increasingly larger scales
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | 1 day ago
this, IMPRS CoNI offers high performance computing facilities for computational modelling and data analysis. The modules covered ensure a structured and comprehensive approach and provide the important basic