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student position (100%) in Computer Vision for 3 years on the topic of offline to online conversion of historical handwritings within the SNSF-funded research project 'Egrapsa: Retracing the evolutions
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focuses on psychometric models (e.g., Item Response Theory models), machine learning methods (e.g., Random Forests, Neural Networks, and interpretation techniques), and multilevel models (e.g., analysis
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PhD student position: elucidating chaperone protein function using single-molecule fluorescence/FRET
several of these areas is desired: Protein biochemistry (purification, bioconjugation, quality control, etc.) Single-molecule experiments and interpretation Advanced data analysis, coding, machine learning
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of econometrics and first experience with statistical programs such as STATA, R, or Python and a high willingness to attain excellent econometrics skills including on machine learning You are fluent in
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experience in several of these areas is desired: Single-molecule experiments and interpretation Advanced data analysis, coding, modeling, machine learning Optics and fluorescence microscopy and/or nanopore
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PhD student position: elucidating chaperone protein function using single-molecule fluorescence/FRET
of these areas is desired: Protein biochemistry (purification, bioconjugation, quality control, etc.) Single-molecule experiments and interpretation Advanced data analysis, coding, machine learning Optics and
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our working and learning environment. Project Description In the framework of the NCCR AntiResist (https://www.nccr-antiresist.ch/en/ ), we are looking for a highly motivated doctoral researcher
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our working and learning environment. Project Description In the framework of the NCCR AntiResist (https://www.nccr-antiresist.ch/en/ ), we are looking for a highly motivated doctoral researcher