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Master Degree or PhD holder in the scope of the R&D Project: FireSys, funded by the European Regional Development Fund (ERDF), through the Innovation and Digital Transition Thematic Programme (COMPETE 2030
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. The successful candidate will be able to teach one of the undergraduate courses related to AI/ML, programming languages, data structures and algorithms, operating systems, network security, visualization, and
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interdisciplinary research across AI hardware, software, and algorithms. AI Accelerators, ML Algorithms, AI Frameworks, and Model-System Codesign have been focus areas in the past - we are always excited to sponsor
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grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. Key Responsibilities: Conduct programming and software development
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Dipartimento di Ingegneria dell'Informazione - Università degli Studi di Padova | Italy | about 1 month ago
immersive and interactive environments. • Definition and modeling of low- and high-level quality-related features. • Development and validation of objective quality assessment metrics for synthesized content
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We are seeking a skilled AI Systems Developer to grow and maintain the University System of New Hampshire AI software platform. The ideal candidate will have strong software engineering skills with
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candidates must thus have a strong interest in algorithmic development as well as embedded hardware integration. Role and responsibilities This PhD project will be executed in close cooperation with
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algorithms from technical sources (e.g., papers, notes, and group discussions) in close collaboration with group members. The work is primarily algorithmic scientific software development: implementing and
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, Purpose of the Job We are looking for one Research Associate to work on the development, implementation and testing of predictive control algorithms for the optimal coordination of available multi-energy
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to advance the project. The successful candidate will have extensive experience developing models and algorithms for analysis of noisy biological data, a deep background in analysis of stochastic processes