Ramin Golestanian

PhD positions are available in Active Matter and Statistical Physics at the Department of Living Matter Physics (LMP) , Max Planck Institute for Dynamics and Self-Organization (MPI-DS) . The research environment is described as vibrant and dynamic, with work focused on applying ideas from theoretical physics to the understanding of living systems. Students will likely engage with a mix of analytical methods and computational methods , with strong relevance to physics and interdisciplinary biology/living systems research. The post is shared by Ramin Golestanian , Director at MPI-DS and Professor at Oxford University. This is a PhD opening ; no postdoctoral or master's opening is indicated. The post does not mention stipend amount, tuition coverage, or specific eligibility requirements beyond the research area and methods. Interested candidates should use the linked institute page for the full job description and application instructions. Application link: https://www.ds.mpg.de/4133384/job_full_offer_26889161

Postdoctoral Researcher positions are available in Active Matter and Statistical Physics at the Department of Living Matter Physics , Max Planck Institute for Dynamics and Self-Organization (MPI-DS) . The group works on applying ideas from theoretical physics to the understanding of living systems, using a broad range of analytical and computational methods . This is a strong fit for researchers with interests in physics , biophysics , and related quantitative approaches to complex living matter. The post was shared by Ramin Golestanian , Director at MPI-DS and Professor at the University of Oxford. The opportunity is for postdoctoral researchers; no PhD or master's opening is indicated in the post. Funding details are not specified in the post excerpt, so applicants should check the official job page for information on contract length, salary, and any additional benefits. To apply, use the official MPI-DS job link and review the full advertisement for the application procedure and required documents.

[Full-time PhD position funded at 2/3 of E13 TVöD Bund for up to three years.] PhD positions are available at the Max Planck Institute for Dynamics and Self-Organization in Göttingen, Germany, within the LMP department led by Prof. Dr. Ramin Golestanian. The project focuses on theoretical and/or computational research in nonequilibrium statistical physics and active matter, with a broader interest in understanding the dynamics of living systems from a physical perspective. The department hosts an active, interdisciplinary environment with group leaders, postdoctoral researchers, students, and visitors. Applicants should hold a Master’s degree (or comparable qualification) in theoretical physics, applied mathematics, or a related discipline from a recognized university. The post is aimed at excellent, enthusiastic, self-motivated early-career researchers with strong communication skills, an interest in nonequilibrium statistical physics and the physics of living systems across scales, and the ability to work in an international team on interdisciplinary topics. Good English is required; German is helpful but not mandatory. The position is full-time and funded at 2/3 of E13 TVöD Bund under the funding guidelines of the Max Planck Society for junior scientists. The appointment is limited to three years, and the starting date is flexible. The institute emphasizes excellent working conditions, work-life balance, health promotion, diversity, and an inclusive environment, and particularly encourages applications from women in areas where they are underrepresented, including theoretical physics. To apply, candidates should use the online application portal and submit a CV, academic records, a statement of research interests, and the contact details of two referees. Applications are processed after the deadline of 1 December 2026, although the institute may continue to receive applications until 1 April 2027 if positions are still open. Early application is encouraged, as appointments may be filled as soon as suitable candidates are identified.