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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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Your Job: Design and development of a modular high throughput sample environment for chemical hydrogen storage investigations under realistic conditions Design, optimization, and testing of sample
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information at: http://www.ifw-dresden.de . The Institute for Metallic Materials (Prof. K. Nielsch) of the IFW Dresden offers Postdoc position (m/f/d) on the following topic: Thermoelectric Energy Harvesters
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of our work: Lauer et al. (2022): Metabolic engineering of Clostridium ljungdahlii for the sustainable production of hexanol and butanol from CO₂ and H₂, Microb. Cell Fact. 21:85 Kottenhahn et al. (2021
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dedicated to advancing the understanding of the molecular mechanisms of hematopoiesis, granulopoiesis, and leukemia development. We also develop innovative gene therapy approaches for hematopoietic stem cell
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, troubleshooting and routine upkeep Develop, optimize and validate sample-preparation and data-analysis workflows for spatial metabolomics, lipidomics and multimodal studies Act as contact for internal and external
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) structures using high energy X-ray methods (scattering, spectroscopy, imaging) Design, optimization, and testing/benchmarking of reactors for operando studies Unravelling of relationships between catalyst
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to translate this knowledge into innovative, optimized vaccine candidates (PMIDs: 35015104, 34990590, 33323394, 30439392; patent: WO2024003343A1). About the Project: You will contribute to a project
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engineering of Clostridium ljungdahlii for the sustainable production of hexanol and butanol from CO₂ and H₂, Microb. Cell Fact. 21:85 Kottenhahn et al. (2021): Hexanol biosynthesis from syngas by Clostridium
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variants on human traits and single-cell readouts. Our research group is pioneering computational methods for deciphering molecular variation across individuals, space, and time. We have a track record in