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Field
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skills and motivation to implement algorithms and test them in practice on large-scale problems. Programming Skills: You are proficient in at least one scientific programming language (such as Python
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this PhD project, you will investigate the co-design between event-based learning algorithms and neuronal hardware units with multi-scale time constants. The algorithmic methodology will exploit recent
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reference architecture for data visiting. This paradigm enables algorithms to securely access and process data within the environments where it resides, supporting federated learning for training machine
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to become a truly global centre of knowledge. Within the Faculty of Science and Engineering, a 4-years PhD position is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial
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interpretable models and algorithms for learning from data. Meanwhile, the field of knowledge discovery and data mining has allowed us to obtain insights from large amounts of data for decades, and it is worth
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and Engineering, a 4-years PhD position is available at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence with the topic of formal verification of distributed systems
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optimizations tailored to different environments. The optimizations range from algebraic optimizations (e.g., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware
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., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware optimizations (e.g., automated pipelining). The PhD student will be supervised by Nusa Zidaric. Key
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., term rewriting) to algorithmic optimizations (e.g., group level algorithms), and to hardware optimizations (e.g., automated pipelining). The PhD student will be supervised by Nusa Zidaric. Key
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experimental testing. You’ll design and run experiments, write and train algorithms, and contribute to open-source tools that may one day become industry standards. This project offers the freedom to explore