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Field
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from chem- and bioinformatics to computer vision and social network analysis. Machine learning with graphs aims at exploiting the potential of the growing amount of structured data in all these areas
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qualified women. About the position The position contains both teaching duties and participation in research projects. The research project topics focus on improving object recognition through computer vision
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to apply Website https://cv.newton-6g.eu/ Requirements Research FieldEngineering » Computer engineeringEducation LevelMaster Degree or equivalent Research FieldEngineering » Electrical engineeringEducation
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art history, excellent English and or German, good computer skills (knowledge of a programming language would be advantageous). Extent of Employment: 30hours/week. Job grading in accordance with
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neuroscience at some point during academic career. Experience handling rodents in a laboratory setting. Computer experience relevant to analysis and documentation of experimental results is essential (Word
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. What you should have: A 1st degree in physics or engineering. An interest in optics, some ability in computer programming A desire to learn new skills in complementary disciplines. You will work jointly
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and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains from chem- and bioinformatics to computer vision and social network analysis. Machine learning with
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for detector support mechanics and cooling, as well as an in-house facility to design, develop and build silicon detectors. At Purdue we also operate a Tier-2 computer center, providing resources for data
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chem- and bioinformatics to computer vision and social network analysis. Machine learning with graphs aims at exploiting the potential of the growing amount of structured data in all these areas
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | 3 months ago
-09731 Requirements Skills/Qualifications Candidate profile - Master degree Computer Sciences. - Experience in scientific programming (e.g., Python, C++, Fortran, Julia) and parallelization