305 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"Helmholtz-Zentrum-Geesthacht" positions in Denmark
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, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system-level programming, developing prototype
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Agent-based simulation and middleware platforms for multi-agent systems AI-driven forecasting and flexibility orchestration Scalable data and machine learning pipelines Digital twin architectures
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, sensing at the robot–environment interface, and bioinspired control strategies to allow the robot to perceive and adapt to different terrains. By bridging soft robotics, physical intelligence, and learning
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labelled images. Close collaboration with the rest of our interdisciplinary team at DTU Construct and Vistacon, particularly the other postdoc position focusing on image analysis using deep learning. Please
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will develop atomistic models and machine-learning potentials to interpret experimental data and predict catalytic performance. The tasks can include Advancing equivariant neural network potentials
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workflows Experience in quantitative data analysis and computational approaches; familiarity with machine learning or advanced statistal methods is advantageous Preferably experience with micro-CT imaging
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on Nanoparticles You will develop atomistic models and machine-learning potentials to interpret experimental data and predict catalytic performance. The tasks can include: Advancing equivariant neural network
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, Bash). Experience working in a Unix/Linux environment, including setting up and managing High Performance Computing (HPC) clusters. Familiarity with metagenomic data analysis and machine learning
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electrical energy storage systems; energy management systems. Experience with data processing, statistical analysis and machine learning techniques is an advantage. Knowledge with Mathworks suite, C/C++ and
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expected to learn new laboratory techniques and become able to use them autonomously. Furthermore, he/she will attend weekly seminars and laboratory meetings. The working hours are 37 hours per week. For