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Field
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planning. On the customer side, the research will focus on how ESG indicators can be meaningfully embedded into portfolio assessments and risk models. For instance, should a construction firm that actively
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explore advanced data structures, Spatial and non-spatial Database Management Systems, and high-performance computing strategies to enable fast, scalable handling of these datasets. You will also
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handling, enabling first-time-right manufacturing. The predictive quality of these tools relies on accurate constitutive models that describe the behavior of the molten material during forming. With
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to relate model structure to outcomes and interpret them in biologically meaningful ways. A collaborative, curious, and creative mindset. Fluency in English (written and spoken; minimally language level C1
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has a long-term involvement in detector construction (the semiconductor tracker, barrel muon chambers, readout, alignment, and data acquisition). For the phase-2 upgrade (2027-2030), we will instrument
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will include boosted final states. The analysis strategy is strongly focused on advanced machine learning techniques, developing attention-based transformer models that will directly classify events from
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the next generation of miniaturized in vitro models to advance regenerative medicine. Your colleagues: A highly interdisciplinary team at MERLN, working within the national MDR consortium. The project Since
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to organ-level outcomes. Your research will clarify how dicarbonyl and AGE (advanced glycation end-product) stress contribute to age-related changes in cardiac structure and metabolism and identify potential
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and research possible. PhD Opportunity: Engineering a Next Generation of Miniaturized In Vitro Models Our goal: Develop the next generation of miniaturized in vitro models to advance regenerative
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brain connectome organization and the integration of this data with recent functional and structural connectome properties and recent evolutionary genetic discoveries, utilizing large-scale bioinformatic