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& AI hardware or brain-inspired AI algorithm development, spatial analysis of multi-omics data. We are particularly interested in applicants with a demonstrated track record of translating discoveries
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via bitbucket). Backup code on bitbucket and oversee the revision of the code to integrate with other algorithms. Algorithm development initially will involve solving problems such as: (1) base calling
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, domain adaptation, multimodal AI) to analyze plant and environmental data. Support the integration of AI algorithms with robotic and sensing systems for real-world deployment. Assist in experimental design
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. Responsibilities: Develop GPU-accelerated dose calculation and optimization algorithms for adaptive HDR brachytherapy. Integrate real-time adaptive planning capabilities into an in-house treatment planning system
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6 Feb 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Computer science » Programming Mathematics » Algorithms Mathematics » Discrete mathematics
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Posting Summary Logo Posting Number STA00188PO26 Job Family Operational Analysis Job Function Business Intelligence USC Market Title IT Technical Trainer Link to USC Market Title https
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the thermomechanical performance of the refractory masonry; Application of advanced statistical analysis algorithms, including sensitivity analyses and comparisons of different algorithm types; Development
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Design and implementantion of automatic calibration techniques for fast tune-up Implementation and benchmarking of quantum algorithms Who we are looking for The following requirements are mandatory: A
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
, or other novel/emerging pollutants - Developing / implementing advance machine learning algorithms for environmental datasets - Attention to detail and careful documentation of work products such as How
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in neuromorphic vision and algorithm–hardware co-design. Prior work includes the design of dedicated neuromorphic architectures for efficient SNN execution Abderrahmane et al. (2022), as