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Field
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quite heavily. We establish new results concerning the analysis of stochastically driven anisotropic fluids, design novel numerical simulation and optimal control schemes, and provide new means for risk
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skills. Strong statistical skills, particularly in experimental design and data interpretation, are highly desired excellent skills in English (C1 level or higher) What we offer: transdisciplinary
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will design climate change mitigation scenarios that respect both climate targets and sustainable development goals using the REMIND model, one of the world’s leading integrated energy-economy-climate
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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 2 months ago
compact, lightweight and robust holographic instruments Develop real-time data pipelines using edge computing, built on our existing toolchain and enhanced with machine learning tech-niques Validate
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evaluation methods for vision models Design metrics to compare neural and behavioral data with computational predictions Collaborate with CRC groups on open, reproducible standards for model evaluation Mentor
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Infection Biology (www.leibniz-hki.de I https://www.leibniz-hki.de/en/ ) have launched the SynThera initiative (www.synthera.eu ) funded by the Carl Zeiss Foundation, which aims to design, create, and deploy
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activities. Your Profile: Master and PhD degree in astronomy, physics, computer science or equivalent fields of study. Proven experience in N-body simulations and the comparison of simulation and observation
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astronomy, physics, computer science or equivalent degree Solid background in star and planet formation or small bodies of the solar system Experience in hydrodynamics and/or N-body simulations in the star
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how homeostasis of immune cell populations – embryonic macrophages are at the center of our attention – contribute to organismal aging. Your Tasks: Design and perform experimental studies using animal
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under small temperature gradients (ΔT ≤ 30 K). Design and Optimize novel fabrication techniques to achieve high packing densities in thermoelectric generators (TEGs) for powering IoT sensor networks