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at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
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philosophy. Subject field Mathematics with specialization in Numerical Analysis. Subject description The subject includes the development, analysis and implementation of algorithms and methods for numerical
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industrial partners and is partly externally funded by the KK Foundation. In co-production with our corporate partners and the community, we develop concepts, principles, methods, algorithms, and tools
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within tissues using our in-house developed spatial transcriptomics-based technology (Spatial VDJ). Using established and newly developed algorithms, we map B cell evolution within tissues, including class
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include the design and implementation of finite element multiscale models and machine learning algorithms, analyzing related experimental data, and collaborating with industrial collaborators to validate
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these questions, we will determine RNA structures in vivo using cutting-edge transcriptome-wide RNA structure probing techniques that together with computational models and machine learning algorithms will generate
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the Tergite software stack, enabling the execution of complex quantum algorithms on our 25-qubit processor. A key focus is automating calibration to ensure reliable single- and two-qubit gate operations, as
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the autumn of 2025 or as agreed. Project description This doctoral position has a special focus on sustainable data cultures, algorithmic decision-making and AI solutions within municipal companies
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layered dependability framework to ensure both safety and security. This involves creating advanced safety control algorithms, system dependency modelling, and fault propagation and traceability methods