Physics
Modul | Content | Scope | Responsible |
---|---|---|---|
12-7-61 |
| 2 SWS V, 2 SWS S, 1 SWS P | Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk |
Micro Systems
Modul | Content | Scope | Responsible |
---|---|---|---|
13-0-19 |
| 2 SWS L, 1 SWS E, | Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk |
Advanced Seminar: Functional Materials
Modul | Content | Scope | Responsible |
---|---|---|---|
Part of 13-0-12 component: 152230 | After successfully completing the module, students are able to prepare and orally present a detailed scientific topic, including an autonomous familiarization with a given scientific problem in experimental physics and the comprehensible oral presentation of a complex topic in a limited time, using well-arranged foils (e.g. power point). Additionally, the ability to participate in a scientific discussions is promoted. The component “Functional materials” is focusing on devices and materials for micro and nano sensor and actuator systems. | 2 SWS | Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk |
Advanced Micro Systems, Focus on Microsensors
Modul | Content | Scope | Responsible |
---|---|---|---|
13-7-52 |
| 2 SWS L, 1 SWS S, | Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk |
Data Exploration and System Management Using Artificial Intelligence / Machine Learning
Modul | Content | Scope | Responsible |
---|---|---|---|
13-0-19 | The subject of the module are the classes of real-world problems that can be solved by data exploration using AI/ML methods. This includes, for example, anomaly/outlier detection, data decomposition and feature selection, data fusion, prediction, decision support. A mapping between problems and available AI/ML methods will be presented. The project consists in solving a self-defined problem using a selected AI/ML technique and computer simulations. The software procedure together with a project report will be created by student | 2 SWS L, 1 SWS P | Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk Durchführung: Dr. hab. Ireneusz Jablonski |
Experimental Techniques in Physics Supported with Artificial Intelligence / Machine Learning
Modul | Content | Scope | Responsible |
---|---|---|---|
13-9-08 | The subject of the module is the fundamentals of experiment design, including the theoretical and practical aspects of experiment planning and execution. This includes, for example, the role of observation and measurement in cognition process, data collection and processing with the use of statistical and AI/ML methods, data and system modeling, computer simulation, and planning of experiment. The laboratory will use computer simulation to solve selected problems of experimentation, e.g. forward and inverse modeling, signal reconstruction, model identification, experiment planning. Statistical and AI/ML techniques will be used in exemplary tasks. The form of the class includes the realization of tasks under supervision and solving self-defined problems. | 2 SWS L, 2 SWS P, | Prof. Dr.-Ing. Dr. rer. nat. habil. Harald Schenk Durchführung: Dr. hab. Ireneusz Jablonski |
Particle-based microfluidics
Modul | Inhalt | Umpfang | Verantwortlich |
---|---|---|---|
13-7-73 |
| 2 SWS V, 1 SWS Ü, |