477 processor-"https:" "https:" "https:" "Dana Farber Cancer Institute" PhD positions in Germany
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for building a career in academia or industry Professional development through JuDocS, including training courses, networking, and structured continuing education ( https://www.fz-juelich.de/en/judocs
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twin of sperm motility, and utilize it to develop a separation method. Your tasks will include: Performing computer simulations and matching them to experimental data Very close collaboration with
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scientific organisation. Where to apply Website https://recruiting.fz-juelich.de/jobposting/61539e3cfcae4675ddacb6ee34238e8ddc0… Requirements Additional Information Website for additional job details https
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Leibniz Institute of Ecological Urban and Regional Development (IOER) • | Dresden, Sachsen | Germany | about 9 hours ago
International PhD peers, staff and supervisors Participation in international conferences Diverse intercultural background of students To find out more about DLGS fellows, see https://dlgs-dresden.de/fellows
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embedded in the Bremen Research Cluster for Dynamics in Logistics (LogDynamics) (http://www.logdynamics.de ). LogDynamics is a cooperative network of research groups from five different departments
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Additional information on beginning, duration and mode of study The starting date of the PhD project is flexible. The initial funding period is usually three years. Find out more at https://www.bgc-jena.mpg.de
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one of the following certificates: TOEFL minimum of 550 (paper-based test), 213 (computer-based), 79 (Internet-based) IELTS minimum of 6.5 CPE minimum level C CAE minimum level C https://www.math
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for more than 12 months in the 3 years immediately prior to the recruitment date. LanguagesENGLISHLevelGood Additional Information Website for additional job details https://rcs.mb.tu-dortmund.de/storages/rcs-mb
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must provide proof of excellent English skills: TOEFL 550 (paper-based), 213 (computer-based), 79 (Internet-based) or equivalent. Application deadline The application deadline has not yet been determined
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/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages