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Field
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-doctoral fellow, you will collaborate with multidisciplinary teams of mathematical, computational, and biological scientists to develop and apply statistical and machine learning methods for analyzing
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discipline) PhD in in Computer Science, Electrical and Electronic Engineering, Mathematics, or a related discipline (or near completion). Recent relevant research experience in machine learning/deep learning
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for improving a healthy lifespan. To reach this goal, we will use machine learning, sonification strategies, mathematical modelling, and experimental systems of cell biology and aging. AUTORHYTHM builds
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traveltime tomography + full waveform inversion) technologies to image the detailed near-surface subsurface structures from tens of meters to a few kilometers. In addition, machine learning techniques will be
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science, or applied mathematics and a strong publication record in machine learning. The candidate will work closely with Dr. Vincent Tan and will use the postdoctoral stint to develop a strong research profile that
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is to decipher the spatiotemporal nature of autophagy and make predictions for improving a healthy lifespan. To reach this goal, we will use machine learning, sonification strategies, mathematical
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-wide in-person events, typically in New York. Basic Qualifications Researchers holding a PhD related to programming languages, artificial intelligence, and machine learning. Researchers with experience
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where appropriate. About You PhD in the broad area of Computer Science/Engineering and/or Applied Mathematics Detailed and highly specialised knowledge and understanding of Computer Vision, Deep Learning
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Job Description The postdoctoral fellow will work closely with Asst. Prof. Patrick Rebentrost in the intersection of quantum algorithms and optimization, machine learning and/or finance. Sample
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degree in computer science, software engineering, mathematics, or a related field. Strong background in multimodal learning, natural language processing, domain adaptation, and knowledge graph