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using advanced LC-MS/MS systems. Maintain and optimize modern liquid chromatography-tandem mass spectrometry (LC-MS/MS) instrumentation. Develop and implement state-of-the-art proteomics technologies
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mechanisms and technical operation into optimal, techno-economic operation strategies) Professional support for PhD students and joint publications in relevant, high-ranking journals Acquisition of research
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Max Planck Institute of Microstructure Physics, Halle (Saale) | Halle, Sachsen Anhalt | Germany | 3 months ago
. Your tasks will include: Materials Development – Designing, synthesizing, and optimizing novel electrode and electrolyte materials for aqueous-based zinc batteries and supercapacitors. Cell Fabrication
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expertise and achieve optimal results. Your Profile A PhD in Bioinformatics, Computational Biology, or a related field. Proven experience in large-scale omics data analysis, preferably MS-based proteomics
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optimize differentiation protocols for germ cells and embryos and apply CRISPR-based genome editing strategies to enhance functionality. 2. Bavarian Pine Vole – A Model for Species Conservation The Bavarian
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development o Utilization of robotics and microfluidic screening devices o Establishing and kinetic model-based optimization of enzyme cascades o Enzyme immobilization • Scientific and
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or application of machine learning/optimization methods Have good English communication skills An exceptional candidate may optionally have one or more of the following experiences: Experience in analyzing spatial
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Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ | Potsdam, Brandenburg | Germany | about 2 months ago
and upper crust, replacing density grids where known regional density files exist Validation, adaption, optimization of existing software written in C++ and Fortran Preparation and update of a user
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Your Job: Responsibility for the design and optimization of manufacturing processes for Wf/W materials, including spark plasma sintering (SPS) and other advanced methods Act as a bridge between
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on the recently published DeepRVAT framework, which leverages advances in machine learning to learn an optimal rare variant aggregation function in a data-driven manner. You will have the opportunity to spend