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computing, networked systems, and beyond. The work will range from theoretical and algorithmic development of distributed protocols and coordination mechanisms, through the design and implementation
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situated in the field of machine learning. Potential research topics include, but are not limited to, algorithmic knowledge discovery, graph mining and social network analysis, optimization for machine
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methods and AI-based approaches. The work builds on and further develops the Meta Attack Language (MAL) , with a particular focus on developing domain-specific models that reflect the concrete actions
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to extract knowledge from data, modelling large-scale complex systems, and exploring new application areas in data science. Areas of interest include but are not limited to models and algorithms for knowledge
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support the teaching activities courses at KTH and further develop methodologies and algorithms for the quantum computer simulators. Qualifications Requirements A graduate degree or an advanced level
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. The work will primarily entail design, implementation, and evaluation of distributed systems and networks for machine learning inference. Applying machine learning concepts, with the goal of devising agentic
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and proteomics to explore fundamental aspects of human cell biology at the single-cell level. Using an antibody-based approach, we systematically investigate how human proteins are distributed in time
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strategies. The position includes collaboration with housing associations, distribution system operators, electricity suppliers, and academic partners, as well as contributions to policy-relevant