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. -Machine learning code generation for autonomous translation of payload data semantics. -Dictionary learning and algorithms for translation between major data modeling languages. -Model-based System
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particular expression with unspecified matrix sizes. When a concrete expression is evaluated at run-time, thus revealing the matrix sizes, an extraction algorithm can identify an optimal evaluation scheme
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role in communication, radar, imaging, and measurement systems. This project focuses on developing advanced theoretical frameworks, algorithms, and methodologies for analysing, designing, and
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diseases from MRI images of the brain and automatic selection of examination type from referrals in radiology. The thesis work will include development of new methods, theoretical analysis, algorithm design
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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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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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within the Research Area of Inflammation at CMM. Develop new analytical algorithms to address complex, high-dimensional data. Engage in local collaborations at Karolinska Institutet and with external
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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