Research Associate and Group Leader
vor 4 Wochen
**Technische Universität Dresden** - **Faculty of Mechanical Science and Engineering, Institute of Materials Science, Chair of Materials Science and Nanotechnology**:
- Technische Universität Dresden (TUD), as a University of Excellence, is one of the leading and most dynamic research institutions in the country. Founded in 1828, today it is a globally oriented, regionally anchored top university as it focuses on the grand challenges of the 21st century. lt develops innovative solutions for the world's most pressing issues. In research and academic programs, the university unites the natural and engineering sciences with the humanities, social sciences and medicine. This wide range of disciplines is a special feature, facilitating interdisciplinarity and transfer of science to society. As a modern employer, it offers attractive working conditions to all employees in teaching, research, technology and administration. The goal is to promote and develop their individual abilities while empowering everyone to reach their full potential. TUD embodies a university culture that is characterized by cosmopolitanism, mutual appreciation, thriving innovation and active participation.
For TUD diversity is an essential feature and a quality criterion of an excellent university. Accordingly, we welcome all applicants who would like to commit themselves, their achievements and productivity to the success of the whole institution.
- Research Associate and Group Leader (M/F/x)
in the field of Machine Learning approaches for Materials Discovery and Data Analysis
The position is starting at the next possible date and limited for an initial period of 3 years with the option of extension to a maximum of 6 years. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz - WissZeitVG). The position aims at obtaining further academic qualification (e.g. habilitation thesis).
**Working field**:
- scientific research work in the field of Machine Learning approaches for Materials Discovery (low-dimensional materials and structures) and Data Analysis (sensor output data) in cooperation with internal and external academic and industrial partners; participation in the acquisition of third-party funding and in the teaching activities of the chair.
**Requirements**:
- excellent university degree, preferably with a PhD degree in Natural or Engineering Sciences; extensive experience in data science, machine learning methods and programming (especially Python). We are looking for a first-class scientist with excellent verbal and written communication skills in English who wants to make a mark in science.
**What we offer**:
- We foster a collaborative spirit essential for making progress on challenging problems. We offer an international and interdisciplinary research environment of high standing and visibility. There will be many opportunities to develop your academic or professional career. We provide the opportunity to acquire teaching skills, project management skills, and team leadership skills.
**How to apply**:
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