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vision, animal welfare, and behavior. The position is aimed at a method-oriented researcher interested in developing and applying computer vision–based methods in real-world settings. The project is part
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. The position is aimed at a method-oriented researcher interested in developing and applying computer vision–based methods in real-world settings. The project is part of the European Partnership on Animal Health
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(https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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at developing new theoretical tools involving scattering amplitudes methods across diverse areas of Theoretical Physics, such as Particle Physics, Cosmology, Quantum Field Theory, Quantum Gravity and String
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statistical skills. 6. Facility working with analysis software. Desirable Qualifications: Computer programing in Matlab, Python, C/C++ or similar. Expertise in machine learning methods and applications
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-depth expertise in Computer Vision and Photogrammetry. - Mastery of state-of-the-art Neural Rendering (NeRF, NeuS, SDF). - Knowledge of Photometric Stereo methods. Operational Skills: - Advanced
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of Languages and funded by an ERC Consolidator Grant awarded to Professor Tuomo Hiippala . The project develops novel methods and resources for studying multimodality, or how humans communicate using
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of electronic devices has a long and successful history of accompanying experimental developments, be it for transistors or memory cells. Nowadays, to be of practical relevance, such technology computer aided
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metadynamics methods. The numerical protocol will be set up on local machines, and data production will be carried out on national supercomputers (CINES, IDRIS). The results of the calculations will then be
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Research Centre (CRC) 1450 “inSight – Multiscale imaging of organ-specific inflammation” (https://www.uni-muenster.de/CRC-inSight) The project is based in the research group of Prof. Dr. Kerstin Steinbrink