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11 Jul 2026 Job Information Organisation/Company Charles University, Faculty of Mathematics and Physics Research Field Computer science Researcher Profile Recognised Researcher (R2) Application
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AITHYRA GmbH - Research Institute for Biomedical Artificial Intelligence of the Austrian Academy of Sciences | Vienna, Virginia | United States | about 14 hours ago
excited by the prospect of working alongside robotics and automated laboratories. a lifelong learner: You have a solid foundation in a quantitative field (computer science, bioinformatics, mathematics
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Engineering, visit rug.nl/fse . The successful candidate will join the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence within the Faculty of Science and Engineering at
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combining theory, research, and design practice Enthusiastic about connecting with people and engaging with real-world societal challenges Willing to contribute to a positive work atmosphere Emphasis will be
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, quantitative, and mixed methodologies—the program seeks to analyze contemporary scenarios, their transformations, and their potential outcomes. This analysis is grounded in general theories of the State and
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components, systems, and the dependencies between them might be captured in a shared structure, and comparing candidate approaches, such as ontologies, knowledge graphs, graph databases, or multi taxonomy
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candidates hold a Master’s degree in Informatics, Mathematics, or a related field, and possess strong expertise in linear algebra, GPU architectures, and programming in C++ and Python. This is a 100% TVL E13
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Engineering, Machine Learning, Applied Mathematics, or a related field. A strong academic background and interest in AI systems, embedded intelligence, edge computing, machine learning, or related areas. Strong
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and acquire those skills and able to deploy them during the course of the project. She or he has a demonstrable interest in optics and electromagnetic scattering, signal processing, and mathematics, as
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physics and building high performance imaging systems. She or he has a demonstrable interest in optics, signal processing, and mathematics or machine learning. The candidate should have an MSc degree in