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] that process information in temporal rather than spatial modes to reduce their footprint. The project involves a collaboration between DTU Electro (Senior Researcher Mikkel Heuck) and Harvard University (Dr
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of the model will largely be built on existing datasets from large scale wave flumes. These datasets will not involve actual swash zone processes, but rather measurements of coastal profile development from
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to new ideas, share our values of scientific curiosity and creativity, be open and honest and conduct research responsibly, be excited about large challenges and enjoy solving them, have an
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algorithms and circuits to enhance imaging quality and speed Creating efficient data acquisition and processing workflows for large datasets of skin nanotexture images Optimizing hardware-software integration
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(for automation, data analysis and ML) and C/C++ (for UDF development and high-performance routines). Hands-on experience running large simulation campaigns in an HPC environment (job schedulers, batch
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metabolic data and correlate NMR readouts with physiological function. Preferred Qualifications: PhD in Bioengineering, Chemistry, Biophysics, or a related field. Extensive hands-on experience with organ-on-a
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Monitoring and Modelling solution for data-driven hOlistic management of urban water quality). At DTU Sustain you will contribute to creating digital solutions that will give urban water managers access to all
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associated with NeAIxt , a Chips JU research project jointly funded by the European Commission and Innovation Fund Denmark (IFD). NeAIxt is a large European collaboration with a consortium of 64 partners
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evaluation using nasal epithelial models and tissue Contribute to in vivo validation in an established mouse model of acute seizures Analyze pharmacokinetics, biodistribution, and therapeutic efficacy data Co
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and interpretation of proteolysis signatures). Apply molecular biology and microbial engineering to investigate functionality of microbial systems, particularly involving large membrane-bound enzymes