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Research Post Doc Fellow
The Advanced Pediatric Brain Imaging Research Laboratory in Diagnostic Imaging & Radiology has an opening for a postdoctoral fellowship position. The research project will focus on in-vivo fetal brain MR image acquisition and analysis of non-invasive perfusion imaging such as Arterial Spin Labelling (ASL) and Blood Level Oxygen Dependence (BOLD BLOD?). Extensive theoretical and practical background in perfusion MRI and/or fMRI is required. Knowledge in software programming using C/C++, MATLAB, and GPU computing is also required.
The Research Postdoctoral Fellow is a “research trainee” for the purpose of enhancing and developing research competencies. The fellow assists faculty in the conduct of research and reports to a principal investigator or CRI Center Director. He or she can serve in several roles in the laboratory setting depending on the scientific specialty and needs of the supported research project. The trainee participates directly in the design and conduct of experiments and therefore needs technical knowledge and subject matter expertise encompassing several disciplines such as molecular and cellular biology, biochemistry, genetics, physiology, or animal science. Based on experience the research post-doctoral fellow may train technical staff, graduate students, and others in laboratory procedures. He or she may provide general supervision in the laboratory and assist with data management and analysis. In addition, the research post-doc fellow will be responsible for assisting the principal investigator in the planning and execution of research projects, grant applications, and publications. The fellow may further assist in the management of resource allocations, and may manage day-to-day activities in the laboratory, such as purchasing, oversight of laboratory animals, radioactivity, and biosafety issues. He or she may guide or lead the work of peers, technicians, or other diverse support staff as necessary to achieve specific assignments or complete large and complex projects.
Candidates must have a PhD in Engineering, Computer Science, and/or Applied Physics/Mathematics. Experience in medical image processing research is preferred.
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