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Master’s degree (or equivalent) in a relevant discipline such as computer science, mathematics, physics, or data science. They should have strong analytical skills related to statistics, machine learning
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project work plan and milestones Your profile Completed university studies (Master/Diploma) in the field of Chemical/Metallurgical/(Mineral) Process Engineering, Data Science, Statistics, Machine Learning
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. The topics are not limited. Information about the available topics and supervisors can be found under the following link: http://scads.ai/positions2025. The location of work (Dresden or Leipzig) depends
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letter Application Application https://www.cens.lmu.de/en/support/career-at-cens/ https://www.cens.de Contact LMU München Center for NanoScience Address StreetGeschwister-Scholl-Platz
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at gsnas.fu-berlin.de Required Documents Required Documents Motivation letter CV Certificates Research expose References Language certificate Application Application https://www.jfki.fu-berlin.de/en
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and mechanical studies of molecular motor proteins at the nanoscale Required Documents Required Documents CV Certificates Motivation letter Application Application https://www.cens.lmu.de/en/support
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academic environment. Required Documents Required Documents CV Certificates Transcripts Language certificate Motivation letter References Application Application https://www.frankfurt-school.de/en/home/study
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at gsnas.fu-berlin.de Required Documents Required Documents Motivation letter CV Certificates Research expose References Language certificate Application Application https://www.jfki.fu-berlin.de/en
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production of bacteria via mass spectrometry Statistical analysis of the resulting data The successful candidate will have the opportunity to work towards a PhD Required qualifications: University degree (M.Sc
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or population genetics/genomics and have a strong interest in studying genetic biodiversity. Previous experience with molecular lab work is a must; additional skills in bioinformatics and/or statistics