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    GRK 3144: Multiscale Imaging and Analytics of Interfaces in Musculoskeletal Health
    The interdisciplinary Research Training Group (RTG) program entitled "Multiscale Imaging and Analytics of Interfaces in Musculoskeletal Health" extends beyond traditional assessments of bone quantity and density to investigate the complexities of musculoskeletal integrity. This program seeks to understand the interactions between bones, muscles, tendons, fat, and vessels, including their interfaces. By integrating biomedical and technological insights, the program aims to drive innovation in diagnostics and preventive healthcare. Its research objectives include exploring the muscle-fat-bone axis, the tendon-bone interface, the role of vascularization in skeletal health, advanced imaging techniques, models for tissue interfaces, and the use of posture and motion as health indicators. Graduates will gain proficiency in state-of-the-art imaging, disease modeling, and machine learning techniques focused on interfaces, equipping them for addressing global challenges in medicine and technology. The Qualification Program is designed to train a new generation of interdisciplinary STEM scientists in musculoskeletal research. Spanning three cohorts over nine years, it emphasizes skill development in interdisciplinary project management, research ethics, and foundational musculoskeletal research knowledge. Networking opportunities are facilitated through workshops, industry excursions, and international conferences. The inclusion of a Mercator fellow position and the involvement of physicians promote international collaboration and research profile development. This program prepares students for careers in research, teaching, and industry, with a strong emphasis on ethical conduct, collaborative skills, and independence. Located in Hamburg, the RTG benefits from the Interdisciplinary Competence Center for Interface Research (ICCIR) and operates across five laboratory campuses in Hamburg-Eppendorf, Hamburg-Harburg, and Hamburg’s Science City Bahrenfeld. The University Medical Center Hamburg (UKE) provides an interdisciplinary research environment, laboratory facilities, and high-resolution imaging tools. The Hamburg University of Technology (TUHH) specializes in engineering sciences, with a focus on artificial intelligence, data analysis, and computational modeling. Hereon, a member of the Helmholtz Association, offers large-scale facilities for synchrotron science and bone interface research. Hamburg's strategic positioning, robust research infrastructure, and collaborative culture create an optimal setting for musculoskeletal research. The RTG is committed to promoting diversity and gender equality, providing support and initiatives for female scientists. Our interdisciplinary approach not only strengthens healthcare and technological innovation but also prepares graduates for significant roles in academic and corporate research sectors, benefiting both the local and global research communities.
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    CRC 1615 - Project B03: Magnetic resonance imaging of large-scale multiphase and reactive flow systems
    In this project, we will develop and use magnetic resonance imaging (MRI) methods which allow to non-intrusively quantify a variety of process variables at high spatial and temporal resolution. The measured variables include the spatial distribution, the velocity, the temperature, and the chemical composition of the phases in the reactor, as well as the pore size distribution and diffusion properties of gels. In numerous collaborations within the CRC, these MRI methods are applied to characterise the material and system components of SMART reactors. The experiments of this project are mainly carried out on a globally unique large-scale vertical MRI system located at the TUHH.
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    CRC 1615 - Central project Z-INF: Big data processing for SMART reactors
    This project integrates the services and research necessary to process the very large amounts of data produced in SMART reactors. For the research part, novel approaches to establish data stream processing in the fog will be developed. A special focus is on integrated solutions which consider aspects like networking quality when setting up a data stream processing topology. The goal is to integrate edge- and cloud-based computational resources in order to process very large amounts of data coming from SMART reactors and similar smart systems.
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