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on a single cell level. This includes single-cell RNAseq datasets and analysis tools, large high-dimensional flow cytometry phenotyping panels and a collection of transgenic mouse models specifically
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For being part of the selection process is needed: University degree (Master/ Dipl. (Univ.)) in a natural science, materials science, or engineering discipline good written and spoken English skills Following
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learning, image analysis, and advanced computing to study relationships between structure and function. Keywords: Human Brain, 3D Atlas, Deep Learning, Temporal Lobe, Brain Function Entry Requirements
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Description TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in the country. TUD embodies a university culture that
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algorithms to compute similarity between interaction interfaces. The PhD candidate will work on substantial improvements of these existing computational pipelines and use them subsequently to discover novel
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conditions chemical analysis of plant secondary metabolites using HPLC-MS and GC-MS protein isolation and characterization using LC-MS plant physiological measurements molecular biological investigations (e.g
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in the STEM disciplines are primarily attributable to the genius of individual visionary figures or rather to synergetic team efforts. Through a systematic analysis of at least 50 key examples from
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to identify targets for the development of rejuvenation strategies. We have established a large dataset of single cell whole transcriptomic analysis of hematopoietic progenitors and bulk RNAseq of endothelial
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into goal-directed behavior. We use state-of-the-art approaches including functional brain imaging, automated behavioral analysis, and computational neuroanatomy. We value a collaborative atmosphere, early
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Description Within the Collaborative Research Center “Wave phenomena – analysis and numerics” (CRC 1173) we are currently seeking to recruit, as soon as possible, a Doctoral Researcher (f/m/d – 75