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of novel algorithms, machine learning for parsing biological data sets (genomics, proteomics, imaging, neuroscience), and related areas at the interface of computer/data science and the life sciences
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Engineers. Serve as liaison with Princeton Research Computing staff on GPU cluster related issues. Professional Development Learn the underlying science, mathematics, statistics, data analysis, and algorithms
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limited to synthetic and chemical biology approaches to cellular computation and biomolecular logic design, the development and implementation of novel algorithms, machine learning for parsing biological
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, at the Assistant Professor rank. We welcome applications from all areas of experimental and theoretical/computational bioengineering. We particularly encourage candidates whose work includes aspects of Device
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with coding and computing; (iii) be able to work independently to solve problems; and (iv) have a long-term interest in economics or finance research. A background in economics or finance is a plus, but
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experience coding in Python and R. Strong understanding of algorithms, data structures, and computational theory. Experience with data analysis and visualization tools to interpret simulation results. Ability
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equivalent experience (e.g. graduate school or industry experience). • Substantial experience coding in Python and R. • Strong understanding of algorithms, data structures, and computational theory
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applications from all areas of experimental and theoretical/computational bioengineering. We particularly encourage candidates whose work includes aspects of Device Bioengineering and/or Computational
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, computers and instrumentation hardware. Ability to install and oversee installation software algorithms for distributed controllers and maintain associated databases. Ability to coordinate maintenance and
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with coding and computing; (iii) be able to work independently to solve problems; and (iv) have a long-term interest in economics or finance research. A background in economics or finance is a plus, but