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Universitat de Vic Master in Omic Data Analysis

Universitat de Vic

Master in Omic Data Analysis

MSc

1 year

English

Part time

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EUR 5,542 / per year

Distance Learning, On-Campus

Key Summary

    About : The Master in Omic Data Analysis focuses on specialized methodologies in genomics, transcriptomics, and proteomics. It integrates statistical and computational techniques essential for analyzing and interpreting complex biological data. The program is designed for individuals aiming to work in the rapidly evolving field of bioinformatics and omics sciences.
    Career Outcomes : Graduates can explore career paths in areas like bioinformatics, genomics, clinical research, and data analysis within pharmaceutical and biotechnology industries. Opportunities also include roles in academia and health informatics, where data-driven insights play a crucial role in research and patient care.

Introduction

The aim of the Master is to produce well-trained professionals in Bioinformatics and Omics Data Analysis who after graduation would be able to perform efficient and rigorous analysis of large amounts of genetic and molecular data in a wide range of applications.

The master responds to the growing use of high-throughput omics techniques, both in the context of biomedical research and in the pharmaceutical and biotechnology industries and to the increasing demand for highly qualified professionals in this field.

The program covers genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics, interactomics, and integromics and provides knowledge of the most important techniques for omic data acquisition and analysis. The students will be able to analyze omics data information using appropriate statistical and bioinformatics tools.

The teaching methodology, in collaboration with research centers and companies in the field, will ensure that a wide range of applications is covered.

General Information

  • Location: BAU, Carrer Pujades, 118 Barcelona (location)
  • Language: English
  • Timetable: 3 pm to 7 pm Monday through Thursday
  • Classes: In-person or online (video lectures), from 15 October to 31 March.
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