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Field
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100%, starting January 2026 (negotiable) Proteins must fold correctly to function, and this process is tightly regulated by a network of chaperone proteins. At the heart of this network is Hsp90, a
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combustion experiments and in particular hydrogen and liquid fuels, image processing, and excellent knowledge of turbulent combustion. Appointment at Research Associate level is dependent on having a PhD
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focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
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to provide everyday supervision to MSc and PhD students in the laboratory. Your role will include support in grant writing and preparing manuscripts for publication. Profile We are looking for a highly
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to understand, predict, and treat diseases. You will work with multimodal biomedical datasets including omics, imaging, and patient data and apply cutting-edge AI models such as graph neural networks, transformer
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to research this topic. Interest in laboratory work and basic technical understanding. Fluent written and spoken English. Programming skills in e.g. Python, R, Matlab and Java. Experience in image processing
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multimodal brain imaging techniques with novel neuromodulation. More specifically, we work to understand the mechanisms of (mal)adaptive plasticity and develop new treatment approaches for different
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motivation to learn, cryo-EM data collection, image processing, and 3D structural analysis. Prior experience with cryo-EM single-particle analysis (SPA) and/or cryo-electron tomography (cryo-ET) is a strong
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Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth
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Medical Sciences is available at the Graduate School’s website: https://healthsciences.ku.dk/phd/guidelines/ Application procedure Your application must be submitted electronically by clicking ‘Apply now