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through a proactive, systematic approach • Ability to work in a team as well as independently • Mechanical design as well as analysis of structural and fluid dynamic engineering problems • Fluent
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | 2 months ago
Job Offer from July 14, 2026 The newly established research group in Phase Transition Engineering (Group Leader: Dr. Leif-Thore Deck) at the Max Planck Institute for Dynamics of Complex Technical
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to deep time and 3) the dynamic lithosphere with emphasis on the Svalbard regional geology and implications for polar areas more widely. About the position This PhD project investigates how permafrost thaw
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evaluation) at one of Europe's leading research universities. The successful candidate will join a dynamic and internationally recognized research group with extensive expertise in microbiome analysis
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PhD in Computational Simulations of Turbulent Reaction Flows for Clean Energy and Sustainable Propul
machine-learning methods, you will analyze flame-turbulence interactions, pollutant formation, as well as unclosed terms relevant to LES modeling. The analysis involves the fluid dynamic as
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Dynamics (MBD) department contributes, using computational methods, to the development of personalized microbiome-based strategies to aid in the detection, monitoring, treatment, and prevention of human
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for recruitment positions for general criteria for the position. Preferred selection criteria Experience with computer vision, video analysis, self-supervised learning, vision transformers, or multimodal learning
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qualities You enjoy combining experimental biology with quantitative approaches and are eager to develop skills in microbiome data analysis and predictive modelling; You have: an MSc degree in plant biology
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, computational analysis, and laboratory research, as well as data compilation, it connects observations from the deep past to present planning and future predictions and explores urbanisation as a non-linear
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nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and