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Field
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/ESA_selects_Harmony_as_tenth_Earth_Explorer_mission ) The candidate will develop and apply cutting-edge remote sensing or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via
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record in machine learning, with preference for expertise in representation learning, deep embeddings, contrastive learning, or foundation models. Solid background in linear algebra, probability, and
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Machine Learning, Deep Learning, Computer Vision, Large Language Models, Data Analytics, or Intelligent Systems will be advantageous. Key Competencies Prior experience in research project coordination and
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such as deep and statistical learning. Experience of executing research projects at the level of senior PhD student, including creating and debugging machine learning algorithem. Excellent communication
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highly desirable. For NeuroAI focus: Proficiency in popular deep learning, computer vision and/or user-interface software frameworks (such as Pytorch, TensorFlow, OpenCV, PyQt, Gradio etc). The candidate
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We are seeking a Research Fellow - Data Science professional with strong expertise in machine learning, deep learning and high-frequency physiological signal analysis. This is a unique opportunity to
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Python and deep learning frameworks (e.g., PyTorch) Interest in applied, industry-collaborative research Where to apply Website https://www.timeshighereducation.com/unijobs/listing/413018/research-fellow
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or photogrammetry methods, in combination with data science approaches such as machine learning and data assimilation via cryospheric models. A main focus of this work is snow and glaciers in the mountains around the
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methodologies or models from an engineering perspective, as well as scientific studies focused on understanding deep learning. This includes the development of novel applications of artificial intelligence
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stakeholders. Key Responsibilities • Develop and validate deep learning and machine learning models for behaviour modelling, including foundation models, graph neural networks (GNNs), and sequence models applied