Перейти к основному содержимому

Modern digital scientific services for researchers

UrFU

Brief description of the course

This course aims to master the capabilities of modern, accessible digital research services for PhD dissertation preparation, grant applications, and publication activities. Upon completion of the course, graduate students will be able to navigate the capabilities of digital research tools and apply them in their own research.

General description of the course concept

The academic discipline "Modern Digital Scientific Services for Researchers" is implemented as an optional part of the main professional educational program of higher education – the program for training scientific and pedagogical personnel in postgraduate studies in all areas of training.

The course "Modern Digital Scientific Services for Researchers" provides a foundation for postgraduate students' research activities in a digital environment at all stages of conducting and administering scientific research.

The objectives of the course "Modern Digital Scientific Services for Researchers" are to develop postgraduate students' skills in using digital services and artificial intelligence technologies at various stages of research, during grant applications, and in applying modern methods for assessing a scientist's scientific performance, mastering academic writing, and publishing technologies, developing a system for promoting scientific results, and developing scientific ethics in the digital age.

Studying this discipline involves completing the following tasks:

  • development of knowledge in the field of scientometric analysis;
  • development of skills in the field of obtaining, collecting and analyzing data from information and abstract databases;
  • training postgraduate students in techniques for the effective use of modern digital services and AI technologies in scientific activities (including those related to the submission of scientific papers to journals; promotion of scientific results and the formation of scientific connections);
  • training postgraduate students in the skills of administering research activities of scientific teams in a digital environment.

The uniqueness of the course

The course is designed to meet the practical needs of graduate students, guides them toward preparing their PhD dissertations during their graduate studies, and explores the attractiveness of professional activities as scientists and teachers engaged in research at UrFU.

Authors of the course

Bagirova Anna Petrovna

Deputy Director of InEU UrFU for Research and Development, Doctor of Economics, Candidate of Sociological Sciences, Professor of the Department of Sociology and Technologies of State and Municipal Administration at the Institute of Economics and Management UrFU

Buntov Evgeny Alexandrovich

Candidate of Physical and Mathematical Sciences, Associate Professor, Senior Researcher at the Laboratory of Scientometrics , Leading Specialist in Project Management at the Department of International Scientific Projects at UrFU

Svalova Tatyana Sergeevna

Candidate of Chemical Sciences, Deputy Director for Science and Innovation at the Chemical Technology Institute at Ural Federal University, Associate Professor of the Department of Analytical Chemistry

Ivanov Alexey Olegovich

Deputy Vice-Rector for Science at UrFU, Chief Research Fellow, Professor at the Department of Theoretical and Mathematical Physics at the UrFU Institute of Natural Sciences and Mathematics

Eroshenko Stanislav Andreevich

Candidate of Technical Sciences, Associate Professor of the Department of Electrical Engineering of the Ural Power Engineering Institute of UrFU

Korelin Andrey Viktorovich

Candidate of Technical Sciences, Deputy Vice-Rector for Research - Head of the Research Department of UrFU

Matrenin Pavel Viktorovich

Candidate of Technical Sciences, Leading Researcher at the Scientific Laboratory of Digital Twins in Electric Power Engineering at the Ural Power Engineering Institute of Ural Federal University

Telepaeva Daria Fedorovna

Candidate of Sociological Sciences, Associate Professor of the Department of Sociology and Technologies of State and Municipal Administration at the Institute of Economics and Management UrFU

Popova Natalya Gennadievna

Candidate of Sociological Sciences, Elsevier expert , Scientific Translation Laboratory

Sandler Daniil Gennadievich

Doctor of Economics, First Vice-Rector for Economics and Strategic Development at UrFU , Head of the Management Department at InEU UrFU

Shulgin Dmitry Borisovich

Doctor of Economics, Candidate of Physical and Mathematical Sciences, Director of the Educational and Scientific Center for Intellectual Property, Head of the Department of Innovation and Intellectual Property at UrFU

Borisov Vasily Ilyich

Candidate of Technical Sciences, Associate Professor of the Educational and Scientific Center "Artificial Intelligence" of UrFU

Khalyasmaa Alexandra Ilmarovna

Candidate of Technical Sciences, Associate Professor, Director of the Research Center for Artificial Intelligence at UrFU, Head of the Scientific Laboratory of Digital Twins in Electric Power Engineering at the Ural Power Engineering Institute at UrFU

Total course complexity

3 credits

Duration of the course

17 weeks

Prerequisites (minimum requirements for the level of preparation)

Experience in conducting scientific research as part of a specialist or master's degree thesis is required.

Target audience

Postgraduate students

Software products and services used in the course

Elibrary, ResearchGate, EBSCO, Ebook, GoogleAcademia, YandexGPT, DeepSeek, GigaChat et al.

Course program

Topic 1. Support for youth science: country, region, university

Topic 2. Russian Presidential Scholarship for Postgraduate Students: Application, Evaluation, and Results

Topic 3. "Priority 2030": research direction

Topic 4. Scientific citation systems – how to get the most out of a dissertation?

Topic 5. Digital services for grant application activities

Topic 6. Artificial Intelligence Tools for Scientific Research

Topic 7. Analytical capabilities of AI in scientific research

Topic 8. Main mistakes in using AI in scientific research

Topic 9. AI-based scientific content generation: specifics by field of science

Topic 10. Academic writing and publishing technologies

Topic 11. Scientometric indicators of journals and the selection of journals for presenting the results of dissertation research

Topic 12. Modern methods of assessing the scientific performance of a scientist

Topic 13. Patent analytics services for researchers

Topic 14. Scientific Ethics in the Digital Age

Topic 15. Legal issues of using AI in scientific research

Topic 16. System for promoting scientific results

Topic 17. Scientific positioning of universities at the global level

Course Summary

  1. Номер курса

    RESDIGSCISERV_EN
  2. Начало курса

  3. Занятия заканчиваются

Внести в список