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Fellow to develop and evaluate artificial intelligence methods for physical medical procedures. The fellow will design and implement machine learning models to analyze procedural data, support clinical
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( https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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( https://www.hsph.harvard.edu/lin-lab/ ), Professor of Biostatistics and Professor of Statistics. The postdoctoral fellow will develop and apply statistical, machine learning (ML), and AI methods
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laboratory environment and following specific clean room protocols Master`s degree in physics or electrical engineering or a related field Willingness to work in laboratory and cleanroom environments
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publishing in peer-reviewed scientific journals Your Profile Master’s degree in electrical engineering, physics, computer science, or a related field Strong academic background in embedded AI and in the
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systems. Your Profile Bachelor’s degree and currently enrolled in a Master’s program in electrical engineering, physics, or a closely related field Basic understanding of device physics, analog/mixed
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. Project description Machine Learning – Algorithms and Theoretical Foundations Recent advances in AI have highlighted the potential of learning systems that make sequential decisions and adapt to
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Primary supervisor Enes Makalic Research area Machine Learning We are interested in understanding genetic variation among individuals and how it relates to disease. To do this, we study genomic
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Primary supervisor Enes Makalic Research area Machine Learning We are interested in understanding genetic variation among individuals and how it relates to disease. To do this, we study genomic
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Documentation of the results What you contribute Electrical Engineering / Mechatronics / Computer Science or related fields Strong interest in machine learning Basic knowledge of Python and common machine