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(primary and hPSCs derived). • Protein Purification. • Tau seed characterization and optimization. • Development and implementation of an in vitro reconstituted model. • Analysis of the effect of tau seed
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, integrating basic research with preclinical and clinical studies. SHIELD offers the opportunity to 16 talented doctoral candidates (DCs) to pursue a PhD within the Network at different universities and
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 2 months ago
aqueous solution. This postdoctoral project focuses on the complexation of Tc in different oxidation states with inorganic ligands. Special emphasis will be placed on the further development
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, or erroneous data, Data cleaning and generation, Development of enhanced loss functions and information-theoretic methods for optimized data analysis, Machine learning-based image segmentation of tomographic
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Build and optimize workflows for analyzing biodiversity and entomological texts, focusing on functional traits, historical context, and geographic scope relevant to current environmental challenges
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) of the U. Politécnica de Madrid, is formed by fifteen researchers and has a long track record of success in research projects for and in collaboration with companies. GPDS develops different lines
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: Synthesis and optimization of PLGA-based nanoparticles and enzymatic nanomotors. Drug loading/release studies in cellular models. Development of patient-derived mucus-secreting tumor-on-a-chip model
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Predoctoral researcher at the Targeted Therapeutics & Nanodevices Research Group (Project BRAINZYME)
, precise transport, controlled release, and therapeutic activity. • Characterize and optimize these biotherapeutics in vitro by assessing their structure, functionality, and stability under storage and
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with companies. GPDS develops different lines of research, in particular the design and development of multisensor acquisition and fusion architectures, applied artificial intelligence and optimization
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to the development of deep learning methods to predict reaction outcomes and optimal reaction conditions for organic reactions. The work will involve model development using Python and/or other programming languages