Research Associate - Dresden, Deutschland - Technische Universität Dresden

Technische Universität Dresden

Geprüftes Unternehmen

Dresden, Deutschland

vor 1 Woche

Geschrieben von:

Lena Wagner

beBee Recruiter

Beschreibung

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.

At the
Center for Advancing Electronics Dresden (cfaed), the
Chair of Network Dynamics (Prof.
Marc Timme) offers a position as

Research Associate / Postdoc (M/F/x)
with focus on
basic research on the nonlinear dynamics of complex systems and networks
starting
October 1, 2023 or later. The position is limited until September 30, 2025. 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.

Tasks:
research on collective dynamical phenomena of complex systems and networks; teaching
introductory material of applied mathematics (for physics students), mathematical modeling and
statistical physics; support of grant proposals, establishing and executing collaborative research.

Requirements:
outstanding university and PhD degree in Theoretical Physics (or closely related field);
experience in mathematical modeling, statistical physics, nonlinear dynamics, stochastic processes;
advanced programming skills; excellent command of English language; high self-motivation and
independent, target
- and solution-driven work attitude; experience in (co-)supervising research;
experience in collaborative research.

What we offer:
You will join a dynamic interdisciplinary team of enthusiastic scientists who pursue
their research agenda by creativity, mutual exchange of knowledge and collaboration across
disciplines and institutions. Your research will be fostered by our philosophy to promote early-career

researchers, which includes:
- access to state-of-the-art research facilities of a leading academic institute
- international doctoral program
- promotion of gender equality and family-friendly work environment
- opportunity to attend training courses (soft skills & skills furthering academic

success/career).
TUD strives to employ more women in academia and research. We therefore expressly encourage
women to apply. The University is a certified family-friendly university and offers a Dual Career
be equally qualified, those with disabilities or with equivalent status pursuant to the German Social
Code IX (SGB IX) will receive priority for employment.

and contact details of two references, copy of degree certificate, transcript of grades (i.e. the official

should be submitted by
July 14, 2023 (stamped arrival date of the university central mail service

Herrn Prof. Marc Timme, Helmholtzstr. 10, 01069 Dresden, Germany. Please submit copies only,
reimbursed.

Reference to data protection:
Your data protection rights, the purpose for which your data will be processed,