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Brandenburg University of Technology Cottbus-Senftenberg • | Cottbus, Brandenburg | Germany | 2 days ago
, Computer Science, Physics, Electrical Engineering and Information Technology Faculty 2 Environmental and Natural Science Faculty 3 Mechanical Engineering, Electrical and Energy Systems Faculty 4 Social Work, Health
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900 EUR per month to meet personal expenses (accommodation, living, health insurance, books). Funding opportunities within the university No Academic admission requirements Master's degree / German
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accommodation, food, health insurance and books are about 1,100 EUR per month. Please note that fees for health insurance may vary according to age. Living expenses might be slightly higher. Students
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the Hamburg metropolitan area. Costs of living We recommend that single students budget at least 900 EUR per month to meet personal expenses (accommodation, living, health insurance, books). Funding
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company health management Ideal conditions for balancing work and private life, as well as a family-friendly corporate policy Flexible work (location) arrangements, e.g. remote work 30 days of annual leave
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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German Cancer Research Center (DKFZ) Heidelberg • | Heidelberg, Baden W rttemberg | Germany | 2 days ago
the fact that PhD students have an academic background in (molecular) biology, (bio-)chemistry, (bio-)physics, mathematics, computational biology, computer science, epidemiology/public health studies, and
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11.11.2024, Wissenschaftliches Personal In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the
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of annual leave and provision for days off between public holidays and weekends (e.g. between Christmas and New Year) Extensive company health management Ideal conditions for balancing work and private life
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) techniques using AI for autonomous inspection and health monitoring of complex infrastructure engineering systems, explicitly identifying information gaps and uncertainties to enhance resilience against