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Science, Computer Science, Data Science, Neuroscience, or a related field by the start date. Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning
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computing systems design and realization, including machine learning (ML) and artificial intelligence (AI) applications including autonomy, sensing and communication, advanced manufacturing, and decision
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datasets with machine learning methods, and software development are beneficial Good organisational skills and ability to work systematically, independently and collaboratively Effective communication skills
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. The selected candidate is expected to teach courses on topics in the field of quantitative finance, machine learning and data science. Courses should be offered in Polish and/or English Academic organizational
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acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical devices Develop hardware-aware machine learning models incorporating electronic and optical
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characterized as an inability to emulate basic human vision skills. Despite significant advances in deep learning-based computer vision systems, many limitations still exist. The main objective of this project is
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: Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical
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Proficiency in written and spoken English, with strong communication and collaboration skills Preferred qualifications Experience with machine learning or statistical modeling Familiarity with high-performance
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, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow
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23 Jan 2026 Job Information Organisation/Company Rīga Stradiņš University Research Field Medical sciences » Health sciences Computer science » Modelling tools Researcher Profile First Stage