200 computer-science-programming-languages-"St"-"FEMTO-ST-institute"-"ST" positions at Leibniz
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collaboration with cooperating institutions and enrolment in a local PhD program Excellent technical equipment, a wide range of experimental methods and a dynamic and interactive research environment Remuneration
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qualifications Successfully completed university degree (master, diploma, or equivalent) in computer science, physics, engineering, mathematics, or comparable field, In-depth theoretical knowledge in Machine
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(FIJI/ImageJ etc.) Ability to work independently and to supervise interns and undergraduates Excellent English (in speaking and writing) and computer skills, knowledge of German is a bonus, but not
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work-life balance Comprehensive program for continuous professional development and further qualification, in the own discipline and beyond Cafeteria with modern recreation rooms Reduced monthly ticket
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machine learning techniques or computational methods for text and data analysis is appreciated The working language of our research team is English; therefore, proficiency in English is essential. While not
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science foundation (DFG). Doctoral students (m/f/d) are facilitated to participate in the doctoral program in order to successfully complete their dissertation. We offer an attractive workplace with
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of human evolution in Southeast-Asia. The project should contribute to the Senckenberg research programme on Biocultural Evolution. Applicants must demonstrate a very good command of English. Your (academic
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science and industry. The Technische Informationsbibliothek (TIB ) – Leibniz Information Centre for Science and Technology – Program Area C, Research and Development, is looking to employ a Java Developer
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intelligence modelling methods and deep learning techniques can also be used in both areas. Your qualifications: Master's degree/diploma/doctorate in computer science, mathematics, physics, engineering, or a
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: development and coordination of the wind erosion monitoring program, the development and adaptation of measurement methods and modelling approaches both in the ZALF part of the project and between the involved