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traversability classification DNN pipeline capable of performing long-term traversability estimation. You will focus on extending our state-of-the-art few-shot segmentation DNN algorithm to enable automatic
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of already implemented methods of the systems towards better performance and visual quality, to adding support for existing 3D frameworks such as the Unity Engine. The task spectrum allows for familiarizing
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unknown terrain conditions, an accurate representation of the environment is essential. For this purpose, data from multiple sensors needs to be interpreted and fused to reliably estimate the traversability
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | about 6 hours ago
institute of the Max Planck Society and is dedicated to the study of human cognitive abilities and brain processes as well as the development of neuroimaging methods. The Brain Networks Group, led by
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well as the management of highly complex multimodal data. This role will focus on providing, developing, evaluating, and productizing computer vision methods for the analysis of video and imaging data that are generated
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looking for a PhD Student (f/m/d) to work on the Development and Evaluation of PET Image Reconstruction Methods for Simultaneous Clinical Dual-Tracer PET Imaging. Positron emission tomography (PET) is a
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processing methods, mechanistic computer models and software tools and to use them in highly relevant clinical, biotechnological and pharmaceutical applications at the forefront of research. All projects
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to the macro-scale, you will explore how the behavior of water-driven materials can be modeled across different scales by computer simulations. Equal opportunity is an important part of our personnel policy. We
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computers, with a focus on partial differential equations (PDEs). Your tasks may include the following: Further development of discretization techniques: Optimize the spatial discretization methods used in
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. Qualifications: • Completed academic university degree (Master level) in mathematics, computer sciences, physics or a related discipline • Knowledge of programming, machine learning methods, mechanistic modelling