Master’s Degree Program “Biomedical Data Science” | Siberian Federal University

Master’s Degree Program “Biomedical Data Science”

The Biomedical Data Science program is a multidisciplinary set of courses which is designed to provide a student with the deep understanding of how the collectible medical data connected with the real pathological processes. It allows to do the detailed analysis and reveal the implicit dependencies between the observed and the hidden medical phenomena.

Medical data analysis is a modern and rapidly evolving practice. It’s in high demand worldwide. Medical data scientists are able to perform common analyses of any personal data types. Therefore, successful obtaining a required knowledge in medical data analysis is almost a 100% guarantee that holders of the Master’s Degree in “Biomedical Data Science” can apply highly demanded positions in many countries of the world.

Aim
The aim of the master’s degree program is to bring up a specialist in the detailed analysis of the various types of medical data. Such a practice has already become one of the most perspective areas of activity, which demands a highly skilled specialists. Master’s Degree Program “Biomedical Data Science” offers a set of courses both for advanced data analysis of arbitrary data and the data from the biological and medical trials. Successful completion of the program will qualify the graduates to apply their skills in medical data centers, academia or insurance sector.

Objectives
During the Program students will get theoretical and practical knowledge in the following main areas:

  • Advanced statistics
  • Machine learning
  • Predictive analytics
  • Electronic health records (EHR) processing

Learning outcomes

Upon completion the students are to achieve the high level of collecting the medical data and its mapping. Students will also acquire the skills in recognition of certain patterns in medical electronic records in order to make the relevant predictions.

The students will be able to apply their knowledge in medicine as the health informatics specialist. Precisely, upon completion of this program, the graduate shall:

  • gather datasets from different patients
  • analyze the electronic health records
  • make a health care analytics
  • design the personalized health prognosis

Relevant links

  • School of Fundamental Biology and Biotechnology of SibFU
  • The program “Biomedical Data Science” of Siberian Federal University is designed by the leading specialists of the university in data science and medical data processing. The University collaborates with the local and Federal medical centers in order to obtain the real-time depersonalized data.

    After the completion of the program, the student will have enough skills to work with the data regardless of its type. This provides a good opportunity to find a well-paid work positions.

    Career prospects

    • The graduates can apply for positions in medical centers as the statisticians or data managers, in insurance companies as data analysts. The possible area of responsibility is not restricted by the medicine – the skills of the graduates will allow to work with the data of any type.
    • There is also a possibility for perspective students to apply for the Ph.D. programs in data science or statistics.

    Teaching Methods
    We are concentrating on the Student-Centered Approach to Learning. The students will be guided through the program courses by providing a certain help in order to find and analyze the information. The topics are usually discussed with the professors to find the full understanding of the information and define the optimal steps to go further.

    Facilities, Equipment and Software
    To reach the highest level in studying the courses of the program, the students will have the possibility to practice in medical data collection in health facilities and discuss this data with medical specialists.

    Master Thesis
    To graduate successfully, the student must complete the master thesis and defend it in front of the dissertation committee. The thesis must include the detailed report of the results of the student’s study with his or her original ideas that were created and investigated during the study.

    Fields of Study: Biomedicine, Data Analysis, Data Visualization
    Duration 2 years
    Starting date September, 1st
    Study intensity Full-time
    Delivery mode Fully online or Blended
    Type of degree M.Sc.
    Credits 120 ECTS credits
    Language of instruction English
    Academic requirements
    • BSc degree in Mathematics or Physics (a copy of your diplomas from previous university studies and transcripts of completed courses and grades) with a strong motivation to work at the interface with biology
    • good command of English: certificate or other official document which confirms the upper-intermediate level
    • Zoom interview
    • a motivation letter and letters of recommendation may also be required
    Tuition fee (per year) The price will be announced soon
    The cost does not include accommodation and living expenses. The price could change at the time of signing a learning agreement.
    Application deadline July 29th
    Accommodation On-campus accommodation is available in double and triple-occupancy rooms (€ 20 per month)
    Practicalities Airport transfer and invitation letter for a Russian study visa are provided by the University


    Andrey Shuvaev

    • Ph.D., Associated Professor at Institute of Fundamental Biology and Biotechnology, Siberian Federal University

    Research interests: biophysics, computational neurophysiology, data analysis
    Google Academy: https://scholar.google.com
    Email: Ashuvaev@sfu-kras.ru

    Program structure


    Study Plan MSc “Biomedical Data Science”
    Courses Exam / credit ECTS credits
    First year
    1st semester
    Basics of Human Anatomy and Physiology Credit 2
    Clinical Data Mining Exam 3
    Advanced Programming Credit 2
    Biosphere and Global Environmental Issues Credit 3
    Methodology and philosophy of Sciences Exam 4
    English for Research Proffessional Communication Exam 5
    Research Seminar Credit 2
    Master's Thesis: Research 9
    2nd semester
    Signal processing Exam 5
    Machine Learning in Biomedical Data Credit 4
    Advanced Programming Exam 4
    Classification of Biomedical Data Credit 3
    Advanced Statistical Methods Credit 3
    Research Seminar Credit 2
    Optional course: Optimization and Data Analysis in Biology Credit 2
    Master's Thesis: Research 5
    Second year
    1st semester
    Predictive Analysis Exam 5
    Machine Learning in Biomedical Data Credit 4
    Classification of Biomedical Data Exam 5
    Advanced Statistical Methods Credit 3
    Elective course: Pattern recognition Credit 3
    Elective course: State-of-the-Art Equipment and Methods for studying Biological Systems credit 3
    Elective course: Processing of Medical Records and Images Exam 5
    Elective course: Advanced Biostatistics Exam 5
    Optional course: Trace kinetics Credit 2
    Master's Thesis: Research 7
    2nd semester
    Master's Thesis: Research 22
    Master's Thesis: Defense 6
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