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key NDT techniques used to inspect metallic and composite materials. These methods generate large 3D datasets that can be difficult for human experts to analyse manually, increasing the risk of missed
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educational background and completed research work. Your application must also contain a plan for your doctoral project which includes: project description plan for the training component progress plan funding
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substantial interest in diverse industrial applications due to its potential for fabricating complex metal structures. This opportunity is centred around improving manufacturing productivity with advanced laser
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Biochemistry Structure and dynamics of photoreceptor proteins using novel methods in time-resolved structural biology. Department of Chemistry for Life Sciences conducts research and education in analytical
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The Center for Intelligent Optics (CIO) develops advanced optical technologies, including imaging, spectroscopy, and laser ablation methods. Our goal is to bridge these cutting-edge laser
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Finite Element Model of the Larva Body: Utilise existing Drosophila larva CT-scan data to segment components such as the cuticle, muscles, and mouth hook. Implement finite element simulations within
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– Adsorption and reaction of small gaseous non-metal oxides on model mineral particles under light illumination. The position is for four years of doctoral studies, including participation in research and
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Max Planck Institute for the Study of Crime, Security and Law | Freiburg im Breisgau, Baden W rttemberg | Germany | 23 days ago
, criminology, behavioral science, or a related field, and a keen interest in bridging theory and application. Experience with advanced research methods—such as experimental designs, longitudinal data
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We are recruiting a PhD student to integrate data-driven methods with NMR spectroscopy to enhance the characterisation of cell culture media and metabolites, increasing throughput and reducing
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training dataset of well-studied volcanoes with known large eruptions, the project will employ statistical and machine learning (ML) methods to identify the strongest predictors of eruption magnitude