Program Overview

MS in Biostatistics - Statistical and Computational Genomics

Program Overview

The MS in Biostatistics with a focus on Statistical and Computational Genomics is a graduate program designed to provide students with a comprehensive understanding of biostatistical principles and their application in genomics research. This program aims to equip students with the skills necessary to analyze and interpret complex genomic data, utilizing statistical and computational methods.

Program Details

• The program curriculum includes coursework in biostatistics, statistical genetics, and computational biology.
  • Core courses cover topics such as statistical inference, computational statistics, and genomics.
  • Elective courses allow students to specialize in areas like bioinformatics, statistical machine learning, and genomic epidemiology.
• The program requires a minimum of [number] credits to graduate, including [number] credits of core coursework and [number] credits of elective coursework.
• Students are also required to complete a [thesis/capstone/project] that demonstrates their ability to apply biostatistical principles to genomic research questions.

Admission Criteria

• Applicants must have a bachelor's degree in a relevant field, such as biostatistics, statistics, biology, or computer science.
• A minimum GPA of [GPA] is required for admission.
• Applicants must also submit [number] letters of recommendation and a personal statement outlining their research interests and goals.
• GRE scores are [required/optional] for admission.

Tuition Fees

• The tuition fee for the program is [$amount] per semester for full-time students.
• Part-time students are charged [$amount] per credit hour.
• Additional fees for health insurance, student activities, and facilities may apply.

Research Areas

• The program offers research opportunities in various areas, including:
  • Statistical genetics and genomics
  • Computational biology and bioinformatics
  • Genomic epidemiology and public health
  • Statistical machine learning and artificial intelligence in genomics

Faculty and Resources

• The program is taught by a faculty of experienced researchers and educators in biostatistics and genomics.
• Students have access to state-of-the-art computational facilities and genomic research laboratories.
• The program also offers opportunities for collaboration with researchers from other departments and institutions.