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candidate eager to operate at the interface of molecular biology, neuroscience, and AI. Responsibilities Wet-Lab & Experimental Work Set up and optimize imaging based spatial transcriptomics protocols.Set up
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development of early warning systems, risk assessment of pathogens; optimization of the calculation of disease burdens, visualization of complex correlations, Big Data analyses, automated analysis of high
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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full ownership of their own research project. Responsibilities Design and execute LC-MS/MS-based proteomics experiments (primarily in negative ion mode) Independently operate and optimize chromatographic
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awareness (SA), like our work on Situational Graphs (S-Graphs), improve on existing techniques by combining 3D environmental maps with detailed knowledge about objects into a single, optimized model. First
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selectivity design and optimization of electrochemical and photoelectrochemical reactors, including basic modeling and simulations in collaboration with theory partners quantitative data analysis and
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findings through functional laboratory experiments Developing and optimizing protocols involving omics methods, immune cell assays, and flow cytometry Close collaboration with biologists, clinicians, and