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of science to society. As a modern employer, it offers attractive working conditions to all employees in teaching, research, technology and administration. The goal is to promote and develop their individual
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models. The scientist will conduct research using machine learning and classical parameterization methods on data from ocean gliders equipped with microstructure turbulence sensors, turbulence resolving
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reliable machine learning-based surrogate models to replace expensive phase field models to simulate failure because of HE. The activities will be complemented by own lab testing e.g., SSRT incl
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academic qualification (usually PhD). Job ID:RTG2947-T7 Title:Microclimatic effects: Weather-robust UAS flight planning and operation Investigators:Dr.-Ing. habil. Judith Rosenow, Chair of Air Transport
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Bioinformatics, Computational Biology, Computer Science, Biomedical Engineering, Computer Engineering, Genetics/Genomics or related field experience with ‘omics platform output experience with biological datasets
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of the central nervous system. Using Drosophila, we study how flexible neural metabolism is and how it adapts to suboptimal conditions, such as malnutrition. Adaptations to nutrient uptake and transport, changes
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schemes a secure job flexible working hours and childcare support the possibility of mobile working an idyllic green campus, which is easily accessible by bicycle, public transport or car free use
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validation, and regulatory reporter assays. Learn more about the group here . YOUR MISSION: Investigate how genetic variants affect male reproductive function Perform single-nucleus and bulk RNA sequencing
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dynamic, highly international team Excellent equipment and a collegial working environment Individual support and promotion of your scientific career through learning state-of-the-art techniques and
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serious disability and those of equal status are particularly welcome. Requirements: • Master's degree in life sciences, computational sciences, or related fields • For biological candidates