TUD Dresden University of Technology, as a University of Excellence, is one of the leading and most dynamic research institutions in Germany.
The Center Synergy of Systems (SynoSys) develops transdisciplinary approaches and methods in the fields of network science, data science and citizen science in order to conduct integrative research on complex phenomena at the interfaces between biomedicine, social sciences and life sciences. SynoSys contributes to the emergence of a scientific vision for healthy human development in which physical and mental health are collectively considered in an increasingly digital and networked social and physical environment. SynoSys is part of the Center for Interdisciplinary Digital Sciences (CIDS), a node in the network of transdisciplinary research on digitalization and a crystallization point for innovation and collaboration with a focus on complex systems science.
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.
The Center Synergy of Systems (SynoSys) offers a position as
Research Associate / PhD Student (m/f/x)
(subject to personal qualification employees are remunerated salary group up to E 13 TV-L)
starting at the earliest possible date with 90% of the fulltime weekly hours and the possibility of increasing to 100% (subject to release of funds) The position is limited until December 31, 2028. The period of employment is governed by the Fixed Term Research Contracts Act (Wissenschaftszeitvertragsgesetz - WissZeitVG). The position offers the chance to obtain further academic qualification (usually PhD). scientific research activities with the general research topic of Post Covid Conditions and a strong interest in analyzing, and integrating large-scale, high-resolution, long-term, individual-based data collected on wearable devices, and survey datasets, as well as modelling to develop, and implement algorithms for identifying complex patterns and phenotypes using machine learning. Furthermore: writing of scientific publications in the relevant Journals; conducting detailed literature searches; participation in professional conferences and presentation of the research work and its projects; support of the center for applications for third-party funding.
university degree in Mathematics, Physics or Computer Sciences, Data Science or equivalent
strong interest in working in a research environment at the interface of computer science, and social sciences as well as data science applications
proficiency in a programming language, like Python or R
experience with machine learning techniques
ability to work in a collaborative interdisciplinary environment
interest in complex systems science and exploratory, high-risk research
good command of spoken and written English
ideally experience with time series data processing and dimensionality reduction techniques
a unique opportunity to do frontier research in a truly transdisciplinary environment with a high-level exposure to various topics
the opportunity for personal qualification in a dynamic and international research environment with a high degree of creative freedom
an interesting and responsible position where you will get to know the diverse tasks and developments in the research field and specific area of expertise
flexible working hours and home office arrangements
diverse offerings for health promotion and work-life balance, for example, through our family office or our health management program
numerous opportunities for further education, including language courses, IT training, and seminars for professional development
possibility to participate in the wide range of activities offered by the university sports program
30 days of paid annual leave and a year-end bonus payment; additional pension provision (VBL)