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challenges facing modern societies. Specifically, the tasks are: Identify state‑of‑the‑art machine‑learning (ML) methods that can be applied to geochemical systems in geological contexts Assess these methods
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profile Completed university studies (Master/Diploma) in the field of Physics (Computational-, Plasma Physics, Optics) or related field Mastery and use of the scientific method Experience in numerical
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or equivalent) in geodesy or a related subject (geophysics, geoinformatics, physics, mathematics) sound experience in applying geodetic space techniques, especially in the analysis of geodetic GNSS measurements
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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. Founded in 1828, today it is a globally
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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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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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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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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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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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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