-
biomedical research laboratory uses human pluripotent stem cells for the study and treatment of diabetes. We have a wide diversity of projects involving stem cells differentiation, genetic engineering with
-
members. Performs other duties as assigned. Required Qualifications Ph.D. in biomedical engineering, rehabilitation science, or a closely related field. Preferred Qualifications Strong background in muscle
-
Addictions, Autism, High Risk Youth, Neurosciences, and Trauma, and the Department is developing innovative new programs in Technology and Mental Health, Global Mental Health, Maternal and Child Mental Health
-
preterm birth. The lab uses innovative and cutting edge experimentation and relies heavily on bioinformatics and biomechanical systems engineering. The successful applicant will utilize clinical research
-
Engineering (AC-STEM, PPMS, PXRD), Chemical and Environmental Analysis Facility (AFM, FTIR), and Department of Chemistry (NMR). In this position, you will contribute to developing and understanding new
-
Job Description Position Summary The Mass Spectrometry Technology Access Center (MTAC) at Washington University School of Medicine, St. Louis has an opening available for highly motivated applicant
-
of genetically engineered mouse models. Research topics center on the control of molecules and materials at the nanometer length scale, and the use of these materials in neuro-oncology applications. Information
-
to manage labor and prevent preterm birth. The lab uses innovative and cutting edge experimentation and relies heavily on bioinformatics and biomechanical systems engineering. The successful applicant will
-
research is aimed at new technology development as well as mechanistic investigation of signaling pathways with the goal of identifying actionable vulnerabilities for therapeutic development in difficult
-
, Biomedical Engineering, Neuroscience, or a related field. Experience with MRI and computer programming languages such as MATLAB, Python, or C/C++. Preferred Qualifications Machine learning, Siemens MRI