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to develop and translate new imaging and therapy methods based on nuclear medicine or fluorescence into clinical use. All our research is driven by developing methods that solve unmet medical needs in patients
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-to-have: Work experience in simulations with proteins/membranes and their analysis Good communication and interpersonal skills Motivation and a collaborative mindset What we provide to you: Open access
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Responsibilities for the role include: Data collection, cleaning, and merging from large-scale microdata sources (e.g., patents, dissertations, bibliometrics). Conduct data analysis using econometric and statistical
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community engagement. In this role, you will: Contribute to research on ecological and spatial data for urban environments: Conducting fieldwork, data collection and analysis related to urban air quality and
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computing protocols known to work with similar plants. Training will be provided as needed and some degree of flexible working is expected to permit this. Data gathering and analysis will be done during, and
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Status: Closed Applications open: 15/05/2025 Applications close: 31/05/2025 View printable version [.pdf] About this scholarship Description/Applicant information This scholarship is funded as part
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studies to aid in the experiment design, impact analysis and icing code droplet impact solver refinement. The main impact of the work will be to provide droplet impact data and analysis at high speeds which
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(coordination) and safety constraints can be intractable. Your work will bridge this gap by providing generalizable, provable design approach that apply across a wide range of networked systems. This 3.5-year PhD
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University of Munich (TUM) , focusing on cutting-edge research in digital health, wearable sensing, and embedded artificial intelligence. The Project title is ‘IoT-based Assisted Living’ and the main purpose
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focus on how interactions between species at different trophic levels shape these responses. The project combines (1) analysis of long-term datasets to quantify historical changes in the distributions