Hochschule Karlsruhe Hochschule Karlsruhe - University of Applied Sciences
Hochschule Karlsruhe Hochschule Karlsruhe - University of Applied Sciences

Institute of Materials and Processes

Profil Projekte Publikationen Team Studentische Forschung

Mitforschen am IMP

Ob Abschlussarbeit, Projektarbeit, HiWi-Stelle oder Erasmus-Praktikum: Am IMP arbeiten Studierende an Fragestellungen aus laufenden Forschungsprojekten – in unseren Laboren und mit Methoden aus Simulation, Experiment und Datenanalyse. Auch Stellen für wissenschaftliche Mitarbeiterinnen und Mitarbeiter schreiben wir hier aus.

Vom HiWi zur Promotion

  1. HiWi-Stelle – erste Erfahrungen in einem laufenden Forschungsprojekt, oft schon ab den ersten Semestern.
  2. Projekt- oder Abschlussarbeit – ein eigenes Thema aus der Forschung, betreut von den Professorinnen und Professoren des Instituts.
  3. Wissenschaftliche Mitarbeit – nach dem Master in einem Forschungsprojekt weiterarbeiten.
  4. Promotion – die eigene Forschung bis zur Promotion vertiefen.

Viele unserer Mitarbeitenden haben genau so am IMP angefangen.

Winter School "Advanced Topics in AI"

The first Winter School "Advanced Topics in AI" of the Faculty of Computer Science and Information Systems took place in mid-February. Master's students with previous knowledge in the field of machine learning were able to deepen their knowledge in the field of Embedded AI.

In the week from 20.02. to 24.02.2023, the first Winter School "Advanced Topics in AI" of the Faculty of Computer Science and Information Systems took place! The event was aimed at master students of the Karlsruhe University of Applied Sciences with prior knowledge in machine learning. It was held by Mickael Cormier from the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (IOSB) / Karlsruhe Institute of Technology (KIT) as a seminar-like lecture with an integrated exercise section.

The topic of this year's Winter School was "Embedded AI", discussing the following contents:
- AI hardware requirements
- Metrics for the evaluation of different hardware architectures
- Properties of different technologies and hardware
- Architectures especially for different classifiers
- Effects of different architectures on energy consumption and processing speed
- Effect of quantization on energy consumption and classification accuracy
- Methods for co-optimization of architecture for implementation of algorithms and hardware

The series of lectures on "Advanced Topics in AI" is organized jointly by the Faculty of Computer Science and Information Systems and the ISRG.

It will be continued in september as part of a Summer School. Further information will be published soon.

Nichts passendes dabei?

Sprechen Sie uns trotzdem an. Gemeinsam schauen wir, woran wir gerade arbeiten und was Sie interessiert und mitbringen – oft ergibt sich daraus ein passendes Thema.

Ausstattung