物理学习理论博士生

Back to News Board Browse in News PhD Theory of Physical Learning 10.08.2026, Academic staff Prof. Karen Alim’s group on Biological Physics and Morphogenesis at the TUM Campus Garching is looking for a theory PhD student (m/f/d) to join our team on the ERC project Learning Matters!. Task You will break with the current focus on the brain to uncover the physics of continual learning instead by investigating the emergence of learning bottom-up in life, reduced in complexity to a network-shaped single cell – Physarum. Lacking any neurons, flows flushing throughout Physarum’s tubular network propagate input packaged as chemical concentration and flow shear force. The tube wall’s viscoelasticity reorganises in response – continually learning its future response. You will develop a theory describing the physical mechanisms of Physarum’s learning mechanics and thereby predict how to implement learning in soft matter, as Physarum’s responsiveness in wall visco-elasticity has its soft matter twin in synthetic hydrogels. Requirements As a suitable candidate, you have a Master’s degree in physics, applied mathematics, or related disciplines. You have knowledge in soft matter/complex systems physics, biological physics, or statistical physics. You enjoy working in interdisciplinary and international teams and have programming skills. In addition, you are able to express yourself confidently both orally and in writing in English. What we offer We offer a two-plus-two-year contract (TV-L E13 75%) with a flexible start date as early as October 2026, in a highly motivated team that combines experimental and theoretical research on equal footing. As an equal opportunity and affirmative action employer, TUM explicitly encourages applications from women as well as from all others who would bring additional dimensions of diversity to the university’s research and teaching strategies. The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. Application We are looking forward to receiving your application documents, which include your CV, your list of publications, a transcript of record, a motivation of your research interests (max. 1 page) and the contact details for two letters of recommendation in one PDF document. Please send these under the subject “PhD Theory of Physical Learning” by e-mail to Prof. Dr. Karen Alim (k.alim@tum.de) latest by 10.09.2026. She will also be happy to provide you with further information in advance. As part of your application, you provide personal data to the Technical University of Munich (TUM). Please view our privacy policy on collecting and processing personal data in the course of the application process pursuant to Art. 13 of the General Data Protection Regulation of the European Union (GDPR) at https://portal.mytum.de/kompass/datenschutz/Bewerbung/. By submitting your application you confirm to have read and understood the data protection information provided by TUM. Prof. Dr. Karen Alim Technische Universität München Ernst-Otto-Fischer-Str. 8 85748 Garching b. München k.alim@tum.de www.bpm.ph.tum.de Bitte geben Sie bei allen Anzeigen eine aussagekräftige Bezeichnung der Aufgabe, eine Beschreibung und durch Komma getrennte Keywords an. Die Bezeichnung 'Wissenschaftlicher Mitarbeiter' ist nicht sinnvoll , da hier nicht erkenntlich ist um welches Fachgebiet bzw. um welche Aufgabe es geht. Eine Anleitung finden Sie in der Kurzanleitung für Stellenanzeigen und (ausführlicher) im Best Practice Manual Stellenanzeigen (pdf) The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. Data Protection Information: When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. 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 in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: k.alim@tum.de More Information https://www.bpm.ph.tum.de Print

As a suitable candidate, you have a Master’s degree in physics, applied mathematics, or related disciplines. You have knowledge in soft matter/complex systems physics, biological physics, or statistical physics. You enjoy working in interdisciplinary and international teams and have programming skills.