777 data-"https:"-"https:"-"https:"-"https:"-"https:"-"Stanford-University" positions in Germany
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(please read the important scholarship information / section F, point 9) Monthly allowance for accompanying members of family. Please also read our important information for scholarship applicants
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Chair of Biological Imaging 10.02.2026, Academic staff We now seek a highly qualified and motivated Post-doctoral researcher (f/m/d) to drive the development of methods for optoacoustic data
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. Motivation, non-academic criteria such as previous professional experience and skills, civic and social engagement, etc. will be considered as part of the selection process. Further information If you are
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at the Institute of Medical Informatics within the research group “Medical Data Integration Center (MeDIC)” led by Dr. Michael Storck and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles
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Integration of simulation and measurement data into interactive or VR environments Data processing, signal analysis, and visualization (e.g. in Python / MATLAB) You are not expected to be an expert in all three
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Course language English and German Current information Application deadlines: 15 March and 15 September Financial support No Structured research and supervision Yes Research training / discussion Yes
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(4DSTEM). This approach will combine three-dimensional charge distribution data, generated through atomistic simulations, with machine-learning-driven modelling to guide and refine the phase reconstruction
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Course location Heidelberg Description/content The Graduate Academy As a coordinating hub for meta-disciplinary skills training, career orientation and information services, the Graduate Academy
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Independent work ethic and desire to learn new methods and protocols A willingness to learn basic computer programming Work well with people from various cultures Ability to speak and write fluently in English
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structured information. Manual analysis is time-consuming and makes it difficult to identify relevant patterns and connections. The I-WASH project aims to support investigators by applying modern ML methods