22 image-coding-"UCL"-"UCL" Postdoctoral positions at Technical University of Denmark
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described through five overall research areas: Diagnostic Imaging, Digital Health, Personalised Therapy, Precision Diagnostics, and Sensory and Neural Technology. Our technologies and solutions are developed
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to computational tools like RFdiffusion, ProteinMPNN, or AlphaFold. Experience with mammalian cell culture in two and/or three dimension Ability to perform biochemical and imaging methods Strong analytical skills
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Tech’s expertise can be described through five overall research areas: Diagnostic Imaging, Digital Health, Personalised Therapy, Precision Diagnostics, and Sensory and Neural Technology. Our technologies
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synergy with another postdoc working on the same project, whose focus is on the development, demonstration and application of the functionalized quartz resonators integrated into a sensor prototype. If
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technological solutions. DTU Health Tech’s expertise can be described through five overall research areas: Diagnostic Imaging, Digital Health, Personalised Therapy, Precision Diagnostics, and Sensory and Neural
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for Biosustainability (DTU Biosustain) Recent progress in our ability to read and write genomic code, combined with advances in automation, analytics and data science, has fundamentally changed the scope and ambition
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Biosustain) Recent progress in our ability to read and write genomic code, combined with advances in automation, analytics and data science, has fundamentally changed the scope and ambition of harnessing
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implementation of these within optimized computer code, but also large-scale applications of the resulting methods to various chemical problems of interest. Candidates with a strong background in theoretical and
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) and geochemical speciation calculations (such as with PHREEQC or a similar code). We are running several projects in parallel, ranging from fundamental investigations of mineral-water-gas properties
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paradigm shift in development of Biologics. A critical challenge preventing this is the current limiting volume of high quality and well-characterized in-vitro T cell immunogenicity data. In this project, we