Positions available
Are you interested in Biological and/or Statistical Physics? Join Us!
Task
Vein networks are a fundamental building block of life. Transport by flow is the main task of these networks – but how well they perform depends on the architecture of the network. We want to discover the physical principles of how vein networks self-organize their architecture – encoded by messengers transported with the flow or even the pressure of the fluid itself. We want to hijack nature’s mechanisms to build optimal transport networks to optimize flow in active pore networks. In an interdisciplinary team, you will either develop theoretical models of the feedback between flow and network architecture or experimentally test the vein network dynamics of our model organism, Physarum polycephalum, synthetic networks, or microfluidic networks. Your findings pave the way for control of vein network architecture and its function.
Requirements
As a Ph.D. candidate, you have an outstanding Master’s degree or comparable degree in biology, physics, applied mathematics, or related disciplines; as a post-doc candidate, you also have a completed doctoral thesis in one of the abovementioned disciplines. A bachelor’s or master’s candidate should pursue a degree in physics, biology, or a related field. Previous research experience is a plus. As an experimental Ph.D. or Post-Doc candidate, you have experience in biological systems and, ideally, in quantitative data analysis. As a theoretical Ph.D. or Post-doc candidate, you know about quantitative biology, soft matter/complex systems physics, or statistical physics. You enjoy working in interdisciplinary and international teams and have programming skills. In addition, you can express yourself confidently both orally and in writing in English.
What we offer
We offer a three-year contract with the possibility of renewal (TV-L E13 75% – doctoral student, TV-L E13 100% Post-Doc) in a highly motivated team, combing on equal footing experimental and theoretical research. As an equal opportunity and affirmative action employer, TUM explicitly encourages applications from women and all others who would bring additional diversity dimensions to the university’s research and teaching strategies. Preference will be given to disabled candidates with essentially the same qualifications.
Application
We look forward to receiving your application documents, including your CV, your list of publications, the motivation of your research interests (max. 1 page), and the contact details for two letters of recommendation in one PDF document. Please send these by e-mail to Prof. Dr. Karen Alim (k.alim@tum.de). Recruiting is ongoing until positions are filled. She will also be happy to provide you with further information in advance.
Data Protection Information:
You submit personal information when you apply for a position with the Technical University of Munich (TUM). With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application following Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged TUM’s above data protection information.