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robust models – and for clinicians, whose goal is to determine when to trust the models. We therefore seek candidates who have strong technical background in working with large-scale deep learning models
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opportunity to be part of large-scale experiments tackling pressing societal challenges. You'll be involved in every stage of the research process—from experimental design to data analysis and publication—while
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landmark database on university deep tech startups, carry out independent, high-quality research leveraging this data, and engage with stakeholders in the Danish and international deep tech arena
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Job Description We are looking for a postdoc who can help establish a national infrastructure for the collection and sharing of biomedical health data in Denmark, named "The Biomedical Data
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interest and documented skills and experience in using computer-based tools to analyse, simulate and predict capture performance of active and passive fishing gears. A track record of publishing in peer
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analyses of large amounts of data generated within biological, biomedical and biotechnological and life sciences area. We strive to gain new knowledge and drive innovation in human, animal, plant and food
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to enhance imaging quality and speed Creating efficient data acquisition and processing workflows for large datasets of skin nanotexture images Optimizing hardware-software integration for robust performance
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observations from the Kepler and TESS satellites, complemented by Gaia data and ground-based spectroscopic and spectropolarimetric observations. See more information here: https://www.space.dtu.dk/english
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and North, ensuring real-world testing across diverse agricultural contexts. Beyond the research itself, IBIS aims to implement standardized experimental protocols, harmonized data formats, and
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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