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20 Sep 2026 Job Information Organisation/Company Aalborg Universitet Department The Faculty of Medicine, Department of Health Science and Technology, Medical Informatics and Image Analysis Research
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At the Faculty of Medicine, Department of Health Science and Technology, one or more PhD stipends in Unsupervised Learning for Medical Image Analysis are available for appointment from November 1
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We hereby invite applications for one or more PhD position focusing on the development and application of hyperspectral imaging technologies for bulk forensic evidence analysis. The project aims
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Danfoss, you will combine thermofluid modelling, reduced-order multiphysics methods, and nonlinear rotor dynamics analysis to develop predictive modelling tools that support the industrial design of
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PhD position in environmental toxicology and endocrine disruption: Focus on new endpoints in zebr...
) in the EU), will be compared to later protected life-stages. Methods include detailed organ histopathology, advanced imaging and spectroscopy, gene expression profiling, behavioral analysis
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other relevant stakeholders. The PhD student will contribute to the prototype development, feasibility test and evaluation of innovative cross-sectoral pathways and will be involved in data collection
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PhD Scholarship in University Students’ Learning Via Digital Twins of Neutron Scattering Instruments
. The digital twins will allow students to perform virtual experiments. ACCESS will make digital twins for ESS instruments on imaging (ODIN), inelastic scattering (BIFROST), small-angle scattering (LOKI) and
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of novel methods to decompose the heterogeneity of psychiatric disorders, particularly ADHD, using large-scale genetic, imaging, and epidemiological data from Denmark and other countries. You will apply
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to molecular hydration. The student will develop experimental methodologies and combine these with state-of-the-art characterization techniques, including Magnetic Resonance Imaging (MRI), Nuclear Magnetic
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Danish health registry data, you will work with spatial data, such as disease maps and medical imaging. Such data are highly informative but also pose significant privacy risks. Your work will focus