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hardware interfacing programming in Python Team-oriented and highly motivated to work in an experimental laboratory A background in quantum computing as well as experience with cryogenics, signal delivery
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programming skills with python Comprehensive knowledge of data science, data analysis, data management as well as machine learning Experience with data-driven machine learning (SINDY, LASSO, SISSO packages
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using geographic information systems (GIS) and programming languages (e.g. Matlab, Python, R) and working with large data sets and data formats, such as netCDF, HDF, including analysis tools such as NCO
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” or Neuroeconomics is highly welcome, but not mandatory Knowledge of neuroscientific methods (fMRI, EEG, MEG or NIRS) and/or in psychophysics would be of great advantage Programming skills in Matlab, R or python and
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, energy sciences, interfaces Experience with programming languages (ideally Python) Fluent in written and spoken English Very independent and self-motivated way of working but also excellent teamwork skills
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disciplines with PhD Extensive knowledge of machine learning/artificial intelligence and big data science Extensive knowledge of programming languages (ideally Python) Basic knowledge of synchrotron research
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conducting work overseas (Africa or Latinamerca) is desirable. • Experience conducting statistical analyses of experimental datasets, and strong analylical skills (proficiency in R, Python, or Matlab
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machine and deep learning Programming experience with Python and Pytorch Strong analytical and problem-solving skills Excellent communication & interdisciplinary skills Fluency in English (written and
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(e.g. Python, R, …). Familiarity to work on a Linux computing cluster (HPC). Preferably experience in working with large medical image data. Vivid interest in the analysis of microscopy images or similar
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with MATLAB, C++, Python or similar ▪ Goal-oriented, independent and structured work style Our offer ▪ Current research topic in a challenging international working environment ▪ Full-time position (TV-L