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18.09.2024, Wissenschaftliches Personal We have several 𝐏𝐡𝐃 & 𝐏𝐨𝐬𝐭𝐃𝐨𝐜 𝐨𝐩𝐞𝐧𝐢𝐧𝐠𝐬 in our Visual Computing & AI Lab in Munich! Topics have a strong focus on GenAI, including 3DGs
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22.10.2020, Wissenschaftliches Personal PhD and PostDoc Positions in Visual Computing & Artificial Intelligence: we are looking for highly-motivated PhD students and PostDocs at the intersection
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, TensorFlow, Pandas), ideally combined with knowledge of data visualization or statistical analysis Knowledge of software development (e.g., Python, Matlab, Simapro), especially in combination with experience
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marine food-webs and ecosystem functioning. By bringing together field observations and mechanistic models, the candidate should specifically investigate how changing lightscapes affect visual predation by
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specifically investigate how changing lightscapes affect visual predation by fish and vertical mobility patterns of fish and plankton, and how the effects propagate down to the base of the food-web. Identified
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Deutsches Zentrum für Neurodegenerative Erkrankungen | Bonn, Nordrhein Westfalen | Germany | about 1 month ago
analysis platforms integrating AI and machine learning pipelines Coding skills in Python or R for data processing and visualization is an asset Fluency in English (spoken and written) Strong scientific
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | about 2 months ago
Access to state-of-the-art scientific infrastructure and training (including imaging, scientific computing and data visualization, proteomics, and electronics facilities, and a mechanical workshop
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-performance computing systems Familiarity with operating systems such as Linux/Unix and proficiency in shell scripting Strong programming skills, preferably in Fortran and Python Competency in visualizing and
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Mantras" project website. This involves mapping and archiving sonic and visual representations of mantras across global Southern Asia, contributing to the design process, refining content, and regularly
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with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D