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National University of Science and Technology POLITEHNICA Bucharest, Pitesti Branch | Romania | about 1 month ago
(machine learning, deep learning); adaptive control and algorithmic optimization; integration of AI models in embedded systems and software platforms. APPLICATION Before applying, all candidates are invited
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offers exceptional opportunities for students to learn from international executives, scholars, and influential thinkers. Graduates join a global network of highly-placed fellow alumni, and in the process
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solutions and applying them in real-world scenarios. Proficiency with machine learning frameworks and pipelines in SKLearn, Numpy, Pandas, and PyTorch. Proficiency with deep learning frameworks such as
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-design. Experience with hardware acceleration (FPGAs, GPUs, SoCs) and low-power design. Familiarity with deep learning frameworks (e.g., PyTorch, TensorFlow) is a plus. Ability to work in an
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leader in dual-sector learning and research by 2028. Join us on the journey and help us achieve our strategic drives embedded in our Strategic Plan 2022-2028: Start well, finish brilliantly. One
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using deep learning or causal learning methods. Candidates must have solid experience with large spatial and temporal datasets, large model manipulation, and HPC. The candidate must also have experience
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the Computer Science program at New York University Abu Dhabi, seeks to recruit a research assistant to work on the intersection of compilers and deep learning. Many companies, such as Google, Facebook, and Amazon
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across a diversity of forest types in Oregon and Washington. Employee will learn about forest succession, tree mortality, and post-fire conditions in mature and old-growth forests of the Cascade Mountains
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Classification Title: AST/ASO/FULL PROF Classification Minimum Requirements: • Ph.D. in computer science or related field • Expertise in AI/ML, deep learning • Expert proficiency in Python, PyTorch
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supporting the academic endeavour from curriculum design to engaging in research/scholarship and providing a student enabling environment. Deep and broad experience in effective clinical teaching and learning