Studying CSE at ETH Zürich — a student's guide
An honest student's guide to the BSc in Computational Science and Engineering (Rechnergestützte Wissenschaften) — written from three years inside the programme.
Why this page
Over the last three years I've received a steady stream of messages from prospective students — mostly from Gymnasium students in Switzerland, sometimes from people considering a switch from another programme. CSE is small (around 80 students per year) and not very visible online, so the same handful of questions keep coming back. This page is my attempt to answer them once, in one place.
None of this is official advice — for that, read the Wegleitung further down, or contact the study coordinator. These are simply my personal impressions as a student in the programme.
Quick answers
What is CSE, in one sentence?
Computer Science + applied mathematics, with an emphasis on simulation, numerics, and using computation to solve problems in physics, engineering, finance, robotics, and the life sciences. We sit at the interface between the Mathematics and Computer Science departments.
Is it more math or more CS?
Slightly more math than the Informatik bachelor, but the math is almost always a means to an end — application-oriented, with proofs playing a much smaller role than in a pure math degree. On the CS side we cover the core (algorithms, systems, parallel programming, numerical methods) but skip most of the "classical" software engineering electives that Informatik students take.
Is it harder than Informatik or Maschinenbau?
All three are demanding ETH bachelors. My honest take: CSE is arguably the most demanding of the three in terms of breadth, because you carry both the math and the CS workload at once. The second year in particular is heavy — set your expectations accordingly.
Why are there only ~80 students per year?
Mostly visibility. CSE is interdisciplinary and doesn't slot neatly into a single high-school subject, so most Gymis never mention it. It is not capped or particularly selective at entry — the basis-year filter does most of the work, as in every ETH programme.
Do I need to be good at chemistry?
No. Chemistry is essentially irrelevant for CSE. Physics, on the other hand, is useful — many simulation courses assume some comfort with classical mechanics, fluids, and ODEs.
What can I specialize in?
From the 3rd year onwards (and in the Master) you have a lot of freedom. Common tracks include Robotics & Control, Computational Finance, Computational Physics / Astrophysics, Quantum, Data Science, and Computational Biology. In practice you can pick from roughly 150 courses across the entire ETH catalogue, subject to a small number of mandatory modules.
What about jobs after CSE?
Very strong. The combination of solid math + solid CS is in demand in basically every quantitatively-serious industry: finance, simulation/engineering, ML research and ML infrastructure, robotics, energy, scientific software, consulting. It's not a "classical engineering job" path the way Maschinenbau is — it's more of a generalist quantitative profile. A meaningful fraction of CSE students continue into a Master or a PhD.
CSE vs. switching from a non-quant programme (e.g. Econ)?
If you specifically want more math and you enjoy programming, CSE is a great fit. If you want quantitative finance in particular, also consider the joint Quantitative Finance Master (ETH/UZH) — it may be a more direct path than rebuilding from a CSE bachelor, depending on where you are in your studies.
If I could give my younger self three pieces of advice
- Take it seriously from week one. Try to do the homework from the start and be active, as the courses build on each other. The course load in the second year is especially demanding.
- Start using your electives strategically in the 3rd year. The catalogue is huge — pick a coherent direction (robotics, finance, ML, physics…) early enough that your bachelor thesis and Master applications have a clear story. Start to think about your electives and how you want to achieve the required credits early on (study the Wegleitung throughly). For example a lot of people take Introduction to Machine Learning already in the 4th semester. Such that they can take Probabilistic Artificial Intelligence or Advanced ML in the 5th semester.
- Get involved in a focus project or a student club. CSE is theoretical by default; the practical skills (Git, Linux, CUDA, ROS, building things end-to-end) come from working on real projects with people, not from lectures.
Heads up: the programme is genuinely demanding, especially in the second year. That's worth knowing before you sign up, but it should not scare you off — the people who finish are uniformly glad they did it.
Official Wegleitung (BSc CSE Guidelines) - last updated: 2026-05-21
This is the official ETH curriculum document for the BSc in Computational Science and Engineering. It lists every required and elective course, credits, and the formal structure of the degree. Read it before making your decision.
Useful links
- BSc Rechnergestützte Wissenschaften — official ETH page
- BSc CSE Wegleitung (latest version on ETH website)
- BSc Informatik study guide — useful for comparison
Last updated 2026-05-21. If something here is out of date or you have a question I haven't covered, please reach out — I'll add the answer to this page.