VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.
AI for Science Seminar
Last Updated: 2026-06-01 11:33:39
Abstract
Artificial intelligence (AI) and machine learning (ML) offer significant potential to revolutionize the fundamentals of scientific computation and discovery today. The goal of this seminar course is to expose student to the recent development of "AI for Science".
Objective
The aim of this course is to showcase how ML/AI techniques can enhance scientific research in the field of Physics/Biology/Chemistry/Mathematics. Students will first learn about relevant scientific models, such as key Partial/Stochastic Differential Equations and their associated dynamical systems. They will also explore various AI methods designed to advance traditional approaches. Furthermore, we will guide students through the actual implementation of foundational algorithms, enabling them to address critical scientific issues hands-on.
Content
1. Introduction to related scientific models. 2. AI methods designed to address the scientific problem. 3. Implementation of some fundamental algorithms.
Resources
Literature
The related papers will be released in the first session of the seminar.
Learning Materials (Links)
- Main link
- Information
General Information
- Language
- English
- Levels
- BSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Registration & Places
- Max Places
- 20
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| seminar |
AI for Science Seminar
Kick-off Meeting: 19.02.25, CAB G 56
Saturday sessions: tba, OAT seminar room
|
|
2 h weekly |