Ricardo Vinuesa

VinuesaLab at the University of Michigan is advertising open research positions in Aerospace Engineering at the intersection of AI for science , flow control , deep reinforcement learning , foundation models , agentic AI , and optimization . The post specifically mentions openings for postdoctoral researchers and summer graduate researchers with the plan to transition into PhD positions . The lab describes its work as advancing aerospace innovation through multidisciplinary research in an international environment. Research themes highlighted in the post include flow control through deep reinforcement learning and foundation models and agentic AI for optimization and scientific discovery . This suggests a strong fit for candidates with backgrounds or interests in aerospace engineering, computational methods, machine learning, and scientific computing. No funding package, stipend amount, tuition coverage, or deadline is stated in the post. The opportunity appears to be a direct lab recruitment call rather than a formal scholarship announcement. To apply, interested candidates should email the poster with the subject line [Join VinuesaLab] or send a direct message. The post does not provide a separate application portal.

Open postdoctoral opportunity in experimental fluid mechanics at the University of Michigan . The post highlights an exciting experimental campaign at the large 5x7 wind tunnel at Michigan Aerospace, with research focused on real-time turbulence control using deep reinforcement learning and metamaterials . The position is being shared by Ricardo Vinuesa (Associate Professor of Aerospace Engineering, University of Michigan) together with Martin Erinin . The ideal candidate is described as an experimentalist interested in advanced flow control, turbulence, and data-driven methods. No deadline, salary, or full application instructions are included in the post itself. Interested applicants should follow the linked “More info” page for details and next steps.