-
, the development and implementation of novel algorithms, machine learning for parsing biological data sets (genomics, proteomics, imaging, neuroscience), and related areas at the interface of computer
-
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
-
, the development and implementation of novel algorithms, machine learning for parsing biological data sets (genomics, proteomics, imaging, neuroscience), and related areas at the interface of computer
-
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
-
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
-
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
-
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
-
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
-
strengths and help expand Princeton's Bioengineering program into new and exciting research areas. Review of applications will begin on November 1, 2025. Applicants should submit online at https