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Field
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motivated and talented doctoral candidate to work on the biophysics of host-pathogen interactions using in vitro model systems mimicking chronic diseases. The project foresees ample collaborative
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will exploit multidisciplinary consortium expertise spanning design, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine
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, energy-related datasets. Proficiency in Python, MATLAB, and/or Julia for modeling, simulation, and data analysis. Familiarity with GIS tools (e.g. QGIS), time-series databases (e.g. InfluxDB), and version
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equipment e.g. STM. Simulating fabrication methods. Collaboration with other groups at NQCP and companies/academic groups in and around the Copenhagen area. Join us in this major confluence of exciting
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. Objectives: -Fabrication, characterization and modeling of the composite magnetic materials. -Modeling, fabrication, characterization and of the embedded power magnetic core inductors. -Implementation
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resource-efficiency requirements. This collaborative doctoral project brings together the Institute of Advanced Simulation – Materials Data Science and Informatics (IAS-9) and the Institute of Energy
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apparatus equipped with thermocouples and thermal imaging to simulate realistic runaway events. Top-performing coatings will be validated in situ on live EV cells under controlled runaway conditions. Dr
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collaborative efforts among researchers at the University of Utah and UC San Diego in developing and applying methods in predictive and causal modeling of complex biomedical and social processes and systems
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powerful, modern analytical techniques including chemical proteomics and metabolomics. They will have access to advanced synthesis facilities, as well as biological models, such as macrophages and organoids
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will be trained in a variety of powerful, modern analytical techniques including chemical proteomics and metabolomics. They will have access to advanced synthesis facilities, as well as biological models