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projects Prior experience in computer vision, image analysis, or machine learning Strong programming skills in Python and experience with deep learning frameworks such as TensorFlow or PyTorch Prior
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PhD studentsin machine learning, computer vision, or a related field to perform an 'industry sabbatical' for 5-10 months. At BCAI we build the foundation to generate real-world impact through cutting
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neuroscience and computer vision (Wolf), and neural recording in free-ranging mouse lemurs in the laboratory (Huber), we aim to investigate key features characteristic of early primate vision. Your profile: A
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Description The research team at the Bosch Center for Artificial Intelligence (BCAI) provides the opportunity for candidates currently enrolled as PhD students in machine learning, computer vision, or a related
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is currently possible. As a part of the Bosch Research Computer Vision Lab and the Bosch Center for Artificial Intelligence in Hildesheim, you collaborate with Bosch as well as with academic research
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Apr 2024 - 18:00 (Europe/Berlin) Type of Contract Permanent Job Status Full-time Hours Per Week 40 Offer Starting Date 20 Mar 2024 Is the job funded through the EU Research Framework Programme? HE
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focus on biometrics, with special emphasis on computer vision and machine learning. As one of our research associates, you will also be part of the National Research Center for Applied Cybersecurity
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into the interplay of 3D generative models and automated 3D scene creation, seeking to redefine the limitations of what is currently possible. As a part of the Bosch Research Computer Vision Lab and the Bosch Center
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frameworkslike PyTorch2) Practical experience in advanced computer vision and deep learning applications3) Knowledge of MATLAB, C/C++ and fluorescence imaging is beneficial but not mandatoryMinimum Qualification
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Max Planck Institute of Animal Behavior, Radolfzell / Constance | Radolfzell am Bodensee, Baden W rttemberg | Germany | 2 months ago
are invisible, dynamic, patchily distributed, and highly unpredictable. The project combines real-life 3D GPS bird tracking and drone and computer vision technology to explore the availability of thermal updrafts