Scholarship: Fully funded
Grade: Bachelor’s degree, Master’s degree
Subjects: Intelligent，informational，integrative，interdisciplinary Fluid-Structure Interaction.
Nationality: All qualified individuals are encouraged to apply.
Location: Canada
Closing date: Open until filled.
Start date: Fall 2021 and Winter 2022 entry.
Scholarship Description:
The i4-FSI Lab (Intelligent, Informative, Integrative, and Interdisciplinary Fluid-Fluid Interaction Laboratory) is at the intersection of fluid mechanics, artificial intelligence, and nature-inspired design. We are interested in combining domain expertise (fluid mechanics, robotics and control) and appropriate machine learning tools to address the inherent spatial and temporal nonlinearity and multiscalarity of fluid-related problems at a larger scale and broader scope.
We envision a paradigm shift in fluid mechanics research towards a physics-based (and informative) probabilistic learning framework, leading to a disruptive technological transformation in the aerospace and marine industry towards a more efficient, safer and greener future. Some of the current research topics include 1) study of aerodynamics and hydrodynamics of fish, bird, insect and mammal locomotion, 2) development of a novel programmable metamaterial for aero/hydro morphology structures, and 3) advancement of machine learning and bio-inspired algorithm for vortical flow control and sensing.
Dixia Fan received his Ph.D. (2019) and M.S. (2016) from MIT in Mechanical Engineering and his B.S. (2013) from Shanghai Jiao Tong University in Naval Architecture, Civil and Ocean Engineering. He is an adjunct professor (2021) at Queens University, Canada, director of the i4-FSI Lab and a faculty member of Ingenuity Labs (https://ingenuitylabs.queensu.ca/). In addition, he is the founder of the MIT Smart Hydrodynamics Lab, which has the world’s first intelligent towing tank (ITT). His research interests focus on physics-based (and informative) machine learning and vortical flow control and sensing, both in fundamental fluid-structure interaction (FSI) problems and in biopropulsion and aeroaquatic maneuvering.
Available topics:
Intelligent，informational，integrative，interdisciplinary Fluid-Structure Interaction.
Eligibility Criteria:
Undergraduate or masters students with experience in fluid dynamics, artificial intelligence and machine learning, robotics design and control, etc., are encouraged to apply, with preference given to those with some research experience. Good reading, writing and communication skills in English are required, as well as a strong sense of teamwork and communication skills.
Application Procedure:
Interested candidates should send their CV, transcripts and specific research interests to [email protected], with PhD student application + name in the subject line.
Queen’s University postgraduate application instructions: https://www.queensu.ca/sgs/prospective-students/application-process.
