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Field
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training and guidance to junior undergraduate and graduate students. Education: A PhD in Neuroscience, Computational Neuroscience, Machine Learning in image analysis, or a related field, with significant
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requirements: PhD degree in Computer Science, Electrical and Electronic Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in
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. The Postdoctoral Fellow will hold a PhD or equivalent degree (e.g., ScD, MD, DVM, DrPH). Under the guidance of Dr. William Pan, the Postdoctoral Fellow will perform full-time, independent research, consistent with
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learning. The post-holder will be familiar with the use of these techniques and experience of dataset construction and data mining will be essential. The successful applicant will have completed an MPhil/PhD
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machine learning tools to physical problems in macromolecular chemistry. Certifications/Licenses Required Knowledge, Skills, and Abilities PhD level is required because creative model design and training is
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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presentation/publication of research findings. Candidates with a Biology and Biomedical Science related Master's degree or DVM degree in addition to a PhD are preferred. This position will require attention
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: Develop novel machine learning theories and techniques for analyzing noisy time-series data, with a particular focus on seismic signals Perform uncertainty quantification in time-series analysis to assess
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position, funded by ALRI, offers an initial one-year appointment, with renewal contingent upon availability of funding. Conducts cutting-edge research in artificial intelligence, machine learning, and data
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training