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to surveillance of infectious pathogens using computer science and mathematics? Join the Delft Bioinformatics Lab and work on graph-based algorithms for microbial genomics! Job description Bacterial and viral
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Do you want to contribute to surveillance of infectious pathogens using computer science and mathematics? Join the Delft Bioinformatics Lab and work on graph-based algorithms for microbial genomics
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space explosion involved in complex systems. The aim of this PhD project is to develop distributed supervisory controller synthesis techniques that are scalable to practical systems. Current decomposition
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application of the approach is limited by the fact that tools for synthesis cannot always deal with the state space explosion involved in complex systems. The aim of this PhD project is to develop distributed
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, with both academia and industry recognising its importance. Distribution is an integral part of innumerous computer systems, providing them with essential improvements to aspects such as performance and
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theory. o SAT, SMT, and CHC solving. o Temporal logic and TLA+. o Distributed algorithms, blockchains, and smart contracts. o Quantum information theory and Markov decision processes. Additional
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. -) SAT, SMT, and CHC solving. -) Temporal logic and TLA+. -) Distributed algorithms, blockchains, and smart contracts. -) Quantum information theory and Markov decision processes. Conditions of employment
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, algorithms and social media? Then apply for this PhD project focused on demystifying algorithmic persuasion by commercial advertisers on TikTok from a differential vulnerability perspective. Who is vulnerable
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participants of the Netherlands Twin Register, integrating genetic and psychological data where relevant. Beyond algorithm development, you will also address methodological challenges such as data quality, bias
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or incomplete. Information Your tasks will include: Developing and benchmarking ML/AI algorithms tailored to low-data regimes — e.g. few-shot learning, transfer learning or data-efficient representation learning