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Field
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The Molecular Plasmonics group at the Eindhoven University of Technology has a PhD position in the field of metasurfaces for single-molecule biosensing. This project aims to develop a new generation
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molecular tools to evaluate the ecological role of parasites and virus in the Elbe Estuary. The work is carried out as part of the DFG Graduate Program “Biota-Mediated Effects of Carbon Cycling in Estuaries
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funded PhD positions. We invite highly motivated candidates to join a dynamic, interdisciplinary research environment, with projects at the forefront of infectious disease and immunology. Successful
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molecular techniques (e.g. qPCR, metabarcoding) to characterise pathogen life cycles, host responses and environmental tolerances. Fieldwork will be conducted at selected coastal sites to assess natural
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Date Posted: 11/05/2025 Req ID: 45877 Faculty/Division: Temerty Faculty of Medicine Department: Department of Molecular Genetics Campus: St. George (Downtown Toronto) Position Number: 00058874
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are expected to provide insights into the fundamental dynamics of molecule-plasmon coupling and contribute to the development of molecular quantum light sources, paving the way for advancements in nanoscale
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at the intersection of biology, and medicine? We’re seeking a talented Scientist to join our dynamic team! Our mission is to develop novel PET imaging agents for widely metastatic cancers and to develop novel
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learning. Experience with the Open Force Field software stack. Experience with the OpenMM molecular dynamics software. A developing track record of peer-reviewed publications in internationally recognised
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Max Planck Institute for the Structure and Dynamics of Matter, Hamburg | Hamburg, Hamburg | Germany | 19 days ago
atomically resolved dynamics, fundamental light-matter interaction, accelerator-based light sources, coherent controlled molecular and solid state dynamics, molecular imaging, extreme timescale spectroscopy
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-harvesting complexes. The research will use a combination of quantum and molecular dynamics simulations, electronic structure calculations, and machine learning approaches. These are similar to earlier work