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Max Planck Institute for Dynamics and Self-Organization, Göttingen | Gottingen, Niedersachsen | Germany | 23 days 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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: completed scientific higher education degree (PhD) in the field(s) of Earth system science, physics, climate physics, geosciences, mathematics, computer science or a comparable field demonstrated experience
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cutting-edge proteomics and phosphoproteomics with computational approaches, we will build a comprehensive molecular framework that links specific inflammatory pathways to clinical phenotypes. Our goal is
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to scientists and investigate possible applications of ML in fields like Chemistry, Numerics, Computational Biology, Astrophysics, Heliophysics etc.. You will be involved in all phases of this process. You will
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: completed scientific higher education degree (PhD) in the field(s) of Earth system science, physics, climate physics, geosciences, mathematics, computer science or a comparable field demonstrated experience
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-responsive proteins to develop genetic switches and circuits in therapeutically relevant bacteria. Your tasks: Use computational tools to design protein structures with desired properties Produce
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on two core but complementary areas: Computer vision and sensor data analysis, applied to tasks such as object detection in drone images (e.g., pest or disease detection), object tracking (e.g. leaves
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possible date at the KlausTschira Institute for Integrative Computational Cardiology to join our interdisciplinary project at the forefront of RNA biology and sequencing technology. Project Overview
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and interest in one of the following fields: • Solid state quantum information science. • Quantum optical properties solid-state systems (e.g. semiconductor quantum dots, colour centers in wice gap
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coding experience with e.g. Python/Matlab/R Practical experience with High Performance Computing, and scientific programming and a willingness to learn to work with high-performing computing systems