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Field
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Overview Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and
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for the position of assistant professor in the project NCN MAESTRO "Challenging problems in partial differential equations inspired by cutting-edge algorithms in statistics and machine learning
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some funding for research travel for the Research Associate/Senior Research Associate. The successful candidate will hold a PhD in mathematics or theoretical computer science by the start of
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literature. Foundational Algorithms for AGI AGI will not emerge from scaling existing models alone; it requires a new algorithmic foundation for learning, reasoning, and adaptation. This research area is
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cortex as a surface, with annotations that point to sites of potential malformation (even before they form). The RA on this project would be required to develop and train novel AI algorithms for extracting
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learning algorithms focused on image data, natural language processing, and tabular data Conduct exploratory data analysis and feature engineering for high-dimensional datasets, including image, text, and
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Innsbruck and help bring quantum computing to its full potential. The ideal candidate has achieved excellent research results in several of the following fields: Quantum algorithms Quantum complexity Quantum
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 8 hours ago
Computer Engineering Fundamentals Algorithms for Computer Engineers Microprocessors Operating Systems Real-Time Systems Computer Security Electrical and Computer Engineering Design Engineering Design II
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spectrometry and programming skills. The position is very suitable for a Master's thesis. Furthermore, the working group plans to establish a PhD position in this field in the course of 2026. Although a
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, PhD, FAIMBE is the director of IGS and is internationally recognized for her work developing predictive models in cancer using spatial multiomics and mathematical tools. Her research incorporates