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comprehensive analysis of complex imaging mass spectrometry datasets (e.g., MALDI-MSI, DESI-MSI) using established computational frameworks Develop and implement novel algorithms and visual analytics for spatial
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some people develop long-lasting sequalae and how these the prognosis vary between phenotypes. Our goals are to: Identify different types of PCC in order to provide more tailored rehabilitation and
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interpretation of results. You will also tailor these analyses in response to clinical and researcher feedback, and help develop new algorithms where needed: this may include the incorporation of genomic or other
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an integrated development of network architectures, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems
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is to combine multi-gene control technology and computer algorithms to develop a foundational discovery platform for future cell programming applications. This position involves both experimental and
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within LTU’s AIC³ Lab (Automation, Industrial Computing, Communication, and Control Laboratory). Subject description The research subject focuses on an integrated development of network architectures
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backgrounds, detector performance, and physics sensitivities. One concrete example is the use of different codes for simulating critical backgrounds, comparing their predictions and developing methods for how
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provides a unique opportunity to work at the intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations
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can reduce model accuracy, especially when modeling multiple processes that interact across different spatial scales. To address this, the project will develop a new class of raster data-processing
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a long-term difference in society. Our most important assets are all the individuals whose curiosity and dedication make Uppsala University one of Sweden’s most exciting workplaces. Uppsala University