Siberian Federal University 
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
- Facebook: facebook.com/StudySibFU
- Skype: StudyatSibFU
- VKontakte: vk.com/international_education_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 |
|
| 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
| 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 | |
