Sentence examples for information technology mathematics from inspiring English sources
To achieve the ambitious task of unraveling the complexity of biological systems in a holistic manner, systems biology requires bridging the gap between various nonbiological disciplines such as information technology, mathematics, physics, and chemometrics.
Bioinformatics is the application of omics science, information technology, mathematics and statistics in the field of biomarker detection.
Clinical bioinformatics is an emerging science combining clinical informatics, bioinformatics, medical informatics, information technology, mathematics and omics science together [47].
The scholarship, S$10,000 per academic year, supports courses such as accountancy, business, computer science, economics, financial engineering, information technology, mathematics, statistics, as well as other approved disciplines.
Since clinical bioinformatics is a multidisciplinary field, which combined clinical informatics, omics science, information technology, mathematics and statistics together, we suggest the cooperation of clinicians and technologists in this field.
Women's under-representation in high-paying jobs in STEM fields (science, technology, engineering and mathematics) mirrors their earlier choices of matriculation electives: male students favour physics, information technology and advanced mathematics; female students favour life sciences.
They found by the final year of school there were large majorities of male students in physics, information technology and specialist mathematics, and large majorities of females in life sciences and health and human development.
More men were pursuing careers in information technology, engineering and mathematics — fields where the ratio of women has barely changed, hovering at less than 20 percent, a Royal College of Physicians report about women and medicine says.
Professionals with backgrounds in technical fields like information technology, computer science, mathematics, and statistics who want to develop applied analytical skills to become a data scientist.
The first domain comprised science, engineering, mathematics, and information technology, with one subdomain comprising life and physical science, engineering, mathematics, and information technology occupations and the other comprising social science occupations.
Secondly, by secondary and tertiary education, vocational training and specific enterprise-based training reoriented towards an increasing emphasis on science, technology, engineering, mathematics and information technology.
