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, Statistics, or related. Strong skills in machine learning and deep learning, with a fundamental understanding of LLMs. Proficiency inPython programmingand major ML/DL frameworks (e.g., PyTorch, TensorFlow
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anthropogenic factors using deep learning and vision transformer models, (2) Incorporating past factor trends for more realistic predictions under the non-equilibrium hypothesis, (3) Leveraging transfer learning
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and dissemination of research findings. Example Projects: Developing deep learning models to analyze spatial single-cell profiles. Using large language models (LLMs) to extract information from
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on the development of deep learning methods for reconstruction and physics analysis of the ATLAS experiment data. The successful candidate will develop innovative analysis methods for the reconstruction or the physics
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students. Qualifications: Required: PhD in Computer Science, AI, Data Science, Statistics, or related. Strong skills in machine learning and deep learning, with a fundamental understanding of LLMs
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of Oslo. via Unsplash Main responsibilities The position is fully embedded (100%) within SmartForest. The main responsibilities include: Developing supervised deep learning algorithms for 3D laser data
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, aiming to transform the care for patients with abdominal aortic aneurysms (AAA). You will develop and validate cutting-edge multimodal deep learning models that integrate imaging and clinical data
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Research Associate to develop and apply scalable artificial intelligence (AI) / deep learning (DL) methods to advance multi-scale coupled physics simulations in support of the missions and programs of the US
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profile PhD in Computer Science, Data Science, Machine Learning, or a related discipline. Proven experience in computer vision (e.g. image processing, deep learning, object detection, segmentation) and
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Post-doctoral Fellow/Senior Research Assistant in the Centre for Information Technology in Education
Psychology, Statistics, or a related field. They should have a deep familiarity with modern test theories, and a strong statistical and computing background. The appointee should also have a high level of