生物流体博士/博士后 (Simulation, Experiment, and/or Scientific Machine Learning)

PhD and/or Postdoc Research Positions in Physiological Fluid Mechanics (Simulation, Experiment, or Scientific Machine Learning): The Artificial Intelligence and Modeling Laboratory for Cardiovascular Diseases (AIMCardio Lab) at Worcester Polytechnic Institute (WPI) is seeking applications for three PhD and/or postdoc research positions. We are looking for highly motivated, collaborative, and enthusiastic researchers with expertise in fluid-structure interaction, computational and experimental fluid mechanics, and/or scientific machine learning, with applications to cardiovascular diseases and medical devices. The initial appointment is for one year, with the possibility of renewal based on performance and funding availability. Successful candidates are expected to commit to a minimum two-year appointment.

AIMCardio Lab conducts cutting-edge research in computational and experimental fluid-structure interaction, cardiovascular biomechanics, digital health, and AI-driven modeling. The laboratory maintains long-standing collaborations with leading hospitals and medical centers across the United States, including the Hospital for Sick Children (Toronto), Children’s Hospital of Philadelphia (Philadelphia), and Columbia University Irving Medical Center (New York). We also collaborate closely with major medical device companies, including Abbott, Edwards Lifesciences, Boston Scientific, and Medtronic, to develop next-generation cardiovascular technologies and translational solutions. More information about our research can be found at: AIMCardioLab.wpi.edu
Required Qualifications
·         Degree in Mechanical Engineering, Biomedical Engineering, Aerospace Engineering, Electrical Engineering, Applied Mathematics, Computer Science, or a closely related field.
o    Bachelor's degree (for PhD applicants) or Ph.D. (or equivalent for Postdoc applicants)

Preferred Qualifications
·         Demonstrated research excellence (through publications for postdoc applicants) in one of the following areas:
o    Experimental fluid mechanics and advanced flow visualization techniques (e.g., Particle Image Velocimetry (PIV), flow imaging, or related experimental methods).
o    Fluid-structure interaction (FSI), computational fluid dynamics (CFD), finite element analysis (FEA), or multiphysics simulations, with strong programming and computational skills.
o    Scientific machine learning, including physics-informed neural networks, operator-learning methods, surrogate modeling, and data-driven modeling of physical systems.
·         Experience conducting research in physiological fluid mechanics and cardiovascular flow systems.
·         Experience contributing to competitive research grant proposals
·         Experience in innovation-driven technology development, intellectual property generation, or commercialization activities (e.g., invention disclosures or patent applications).
·         Strong mentoring skills and a demonstrated ability to supervise graduate students and undergraduate researchers.
·         Excellent written and verbal communication skills and the ability to work effectively in interdisciplinary research teams.

What We Offer
·         Opportunities to work on high-impact projects at the intersection of cardiovascular biomechanics, artificial intelligence, and translational medicine.
·         Access to state-of-the-art computational and experimental research facilities.
·         Extensive collaborations with leading clinicians, researchers, and medical device companies.
·         A highly interdisciplinary and supportive research environment with strong opportunities for career development in academia, industry, and entrepreneurship.

Application Instructions: Applications will be reviewed on a rolling basis until positions are filled. Please submit all materials as a single PDF file to ZWei1@wpi.edu with the subject line: “Application – [Area of Expertise]”
·         Curriculum Vitae (CV)
·         Academic transcripts (Bachelor’s, Master’s, and Ph.D., if applicable)
·         Three representative peer-reviewed journal publications (full PDF versions)
·         Contact information for three professional references