Teaching Positions for the 2026/2027 Academic Year
We believe that in the 21st century, everyone should be more than just "experienced PC users" – beyond that, you need to be digitally literate, understand the basics of programming, and be able to analyse data.
The Data Culture project at HSE University teaches all students these essential skills.
💫 We invite you to join the project's teaching team! 💫
- Digital Literacy and AI;
- Python for non‑IT students;
- Data Analysis.
What will you be doing?
- Deliver classes according to the course schedule in one or more HSE University buildings (over one or two modules – a quarter or a semester);
- Prepare for classes: develop teaching materials (presentations, quizzes, tests, group assignments), study the theory;
- Organise the course: set deadlines, prepare and discuss homework, tests, exams, etc. together with other instructors;
- Grade assignments and assess students using established rubrics, conduct assessments and retakes under the guidance of a methodologist;
- Supervise the work of teaching assistants;
- Collaborate with other instructors, the methodologist, and the project team;
- Answer students' questions outside class hours, hold consultations (online is fine);
- Motivate students to engage with the course, explain why these skills matter, and provide moral support during challenging courses (for most non‑specialist students, Data Culture courses are very, very challenging!).
What will I gain from participating?
- You'll gain new experience and try your hand at teaching;
- You'll stay connected to the student community;
- You'll learn how to explain complex ideas in simple terms and support students;
- You'll be inspired – our students are great, it's a pleasure to work with them, and you'll feel part of a vibrant community;
- You'll see your own work from a fresh perspective;
- You'll receive fair compensation for your work ;)
What we expect from applicants:
- A higher education degree;
- Willingness to complete mandatory training;
- Ability to connect with an audience and explain complex topics simply;
- Desire to grow and learn new things;
- Responsibility and organisation;
- Familiarity with modern educational technologies;
- Technical competences:
For Digital Literacy and AI: basic knowledge of computer science and working with computers. An understanding of how generative neural networks work and the ability to critically evaluate their outputs is essential. We expect you to not only explain the AI phenomenon but also teach students how to use modern AI tools for applied tasks (study, work, daily life) while maintaining critical thinking and awareness of ethical limitations. This discipline is suitable for those who are not IT specialists but would like to dive into this field.
For Python Programming: knowledge of basic Python syntax at an intermediate level or higher; strong critical, logical, and algorithmic thinking; industry experience is a plus. This discipline suits both those who have independently completed an introductory programming course and want to pass on their knowledge, and those working in the industry who want to try teaching and share their experience.
For Data Analysis: understanding how to collect, process, and visualise data using Python data analysis libraries. Ability to interpret analysis results and draw data‑driven conclusions. Ability to formulate statistical hypotheses and conduct tests to verify them. Knowledge of core machine learning algorithms such as linear regression and logistic regression. Familiarity with libraries: numpy, pandas, matplotlib, seaborn, scipy, statsmodels, scikit‑learn.
- Teaching experience is welcome but not required.
When and how does it work?
Courses may last 2, 3, or 4 months (rarely longer) – for example, from September to December, or from mid‑January to the end of March.
Course preparation begins several months before the start. If your course starts in September, we'll introduce you to the teaching team and begin preparations around June.
Most courses have been running for several years – they already have syllabi (which you can improve) and materials (which you can also improve!). All we need is instructors.
- the course team – instructors teaching the same discipline in other groups;
- an expert you can turn to with questions like "How was this done before?" and "What's the best approach?";
- teaching assistant(s) – students you will choose yourself. They have already taken similar courses and succeeded. They'll handle routine tasks (creating chats, grading homework, etc.);
- a manager who will guide and assist you through all processes.