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Institution profile

Czech Technical University In Prague

CzechiaEurope

#416

QS World University Rankings 2026

36.5

QS 2026 overall score

QS World University Rankings data

Ranking data

QS World University Rankings source

#416

QS World University Rankings 2026

#420

QS World University Rankings 2025

36.5

QS 2026 overall score

QS 2026 indicators

Indicator-level data

Each card keeps the QS 2026 score and rank separate. A missing value is not estimated.

Academic reputation

QS 2026 score
26.8
QS 2026 rank
#468

Employer reputation

QS 2026 score
51.3
QS 2026 rank
#243

Faculty-student ratio

QS 2026 score
89.4
QS 2026 rank
#107

Citations per faculty

QS 2026 score
6.2
QS 2026 rank
#801

International faculty ratio

QS 2026 score
28.7
QS 2026 rank
#598

International student ratio

QS 2026 score
56
QS 2026 rank
#374

International student diversity

QS 2026 score
60.2
QS 2026 rank
#341

International research network

QS 2026 score
69.4
QS 2026 rank
#542

Employment outcomes

QS 2026 score
23.1
QS 2026 rank
#670

Sustainability

QS 2026 score
53.6
QS 2026 rank
#630
University profile

About Czech Technical University In Prague

Czech Technical University public routes link scientific workplaces, research services, partnerships, and technical news

Czech Technical University in Prague presents research through science and research routes, unique scientific workplaces, InQbay, a Patent Centre, a central library, journals and magazines, university alliances, partners, and technical news. These entries identify different parts of a research environment. A scientific workplace can point to a specialised setting. A library or journal route can lead to documented work. An innovation or patent route may relate to translation beyond the university. An alliance or partner page can indicate a public relationship. A news item can introduce a concrete activity. None of these categories automatically supplies the same kind of evidence about a research question, so the source closest to the object should carry a precise claim.

The homepage's reports also include an AI tool developed by a student at the Faculty of Electrical Engineering and Computer Science, photonics activity, motion-planning methods, and technical learning events. These are useful subject cues, but a term such as AI, electrical engineering, photonics, or motion planning still has to be narrowed. An AI question may involve a model, data, task, evaluation, interface, or use context. A photonics question can depend on an optical system, material, measurement, instrument, or signal. A motion-planning question may require a robot or vehicle, environment, constraints, sensing, algorithm, simulation, and physical test. A local record must show which of those elements is actually present.

CTU AeroLab makes aircraft design, payload, speed, testing, and competition constraints visible

The CTU AeroLab student team offers a detailed public example from the Department of Aircraft Engineering in the Faculty of Mechanical Engineering. In the Air Cargo Challenge, the stated task was to move the largest possible payload while achieving high flight speed. The team developed an aircraft called MLOK and the report describes performance across several flights. This is useful because it identifies a technical object, a clear set of constraints, and observable outcomes. An aircraft-design question could concern airframe structure, propulsion, payload, mass, flight speed, stability, control, aerodynamics, materials, manufacturing, sensors, or test conditions. Each version would need different technical evidence.

The team also participates in design competitions and mentions a future autonomous-flight challenge. Competition reports can show a real test context, but they may not provide the complete design model, calculation, code, test log, or engineering rationale. A reader should therefore use the story to find the closest local record about the aircraft, laboratory, team, or engineering work. If the question is about autonomous flight, the relevant evidence might include sensing, navigation, control logic, motion planning, simulation, safety conditions, and validation. If it is about payload performance, the emphasis might be on aerodynamic design, mass distribution, structural behaviour, propulsion, flight data, and the rules of the test.

Make a CTU technical question specific enough to choose a laboratory, team, publication, or research route

A careful Czech Technical University search begins with the engineering object and the material needed to study it. For an aircraft problem, name the component, flight condition, payload, control task, sensor, material, model, or test. For an AI problem, specify the input, task, data, algorithm, evaluation, and system context. For a photonics question, identify the light source, optical element, material, measurement, image, signal, or application. This short plan helps a reader decide whether to follow a scientific workplace, faculty team, technical report, library record, journal, news item, or partnership route. It is a more reliable process than linking a broad technical keyword to an entire university.

The official CTU pages establish a public technical research structure and one detailed aircraft-team example. They do not confirm that a given laboratory is currently pursuing a new question, that a competition story gives every design detail, or that a partnership or innovation route describes a particular method. A narrow conclusion needs a local official page that connects the object to a stated activity and evidence. When the available material stays high-level, it should be retained as a relevant lead for further review. This preserves the value of CTU's public technical information while respecting the difference between a visible route and proof of a specific research fit.

Institution record

Country
Czechia
Region
Europe
Status
Public
QS size code
L
Profile record updated
July 24, 2026

This date shows when this profile was refreshed. It is not a source-verification date from QS or the university.

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