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experience applying algorithms to solve problems in areas like NLP, Computer Vision, or on tabular data. Generative AI & LLMs: Hands-on experience developing LLM-powered applications, including Prompt
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
computer vision algorithms into the NICE Toolbox. Assist with testing, evaluation, and optimization of implemented computer vision methods. Provide basic user support for researchers using the NICE Toolbox
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software development, modern software languages, cloud technologies, databases, and algorithms. Experience with data analytics, artificial intelligence, and machine learning is a plus. The individual must be
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imaging, medical signal processing, beamforming, image reconstruction, elastography, Doppler imaging, or computational imaging. Demonstrated experience in algorithm development and scientific programming
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identity records using profile matching algorithms and manual review. Collaborate with the Identity Services team to keep the university master identity model consistent. Metadata & Taxonomy Management
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research across a wide range of disciplines including mathematics, the sciences and computer science, with an emphasis on the theoretical foundation of machine learning, new algorithms and AI for Science
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the sole discretion of the University. Essential Duties and Responsibilities include the following. Other duties may be assigned. 1. Research, develop, validate, and deploy AI models, algorithms, and data
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About the Opportunity Job Summary The department of Electrical and Computer Engineering and Institute for Intelligent Networked Systems (INSI) is seeking a Postdoctoral Research Fellow to work
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evaluate computer vision and machine learning algorithms empirically. Author research articles at an international level for peer-reviewed conferences. Engineer software based on the research outcomes
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interdisciplinary degree between Music and Technology degrees (e.g., Electrical and Computer Engineering). Students gain musical training through a musicianship core, applied musical instrument study, and a musical