Title Instructor in Orthopedic Surgery Institution Massachusetts General Hospital Department Orthopedic Surgery Address Massachusetts General Hospital 55 Fruit St Boston MA 02114
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Biography
MGH, Boston, MA | Postdoc | | Orthopaedics |
Rice University, Houston, TX | Postdoc | 10/2018 | Mechanical Engineering |
Auburn University, Auburn, AL | Ph.D. | 08/2017 | Mechanical Engineering |
Tehran Polytechnic, Tehran, Iran | BSc | 07/2012 | Civil Engineering |

Mentoring
Available: 01/10/22, Expires: 03/01/24
The Skeletal Oncology Research Group (SORG) at the Department of Orthopaedic Surgery at Harvard Medical School and the Massachusetts General Hospital is seeking multiple motivated individuals for Research Fellow positions starting from Jan 2022 to work on MGB orthopaedic registries. Interested researchers will be involved in development of AI-based models across a range of orthopaedic subspecialties including trauma, spine, tumor, shoulder, and arthroplasty for the Mass General Brigham Healthcare network of hospitals. The researcher will also assist the team with several aspects of the ongoing clinical and translational research at SORG. Please check The SORG website for more detailes about our team (https://sorg.mgh.harvard.edu/). The research fellows are also welcome to join the engineering team at Center for Physicial Artificial Intelligence for the development of biomedical devices and wearables that is the other focus of the labs. The mission of SORG and CPAI is to improve patient outcomes through clinical research and engineering in Orthopaedics. The applicant will be working under the supervision of Dr. Joseph Schwab, chief of spine surgery, director of MGB orthopaedic registries, director of SORG, co-director of Stephan Harris Chordoma center, and Dr. Hamid Ghaednia, Co-Director of SORG and MGB Registries in a very collaborative environment. This position would provide an excellent opportunity for transition to independence by writing several grants, understanding the clinical challenges in orthopaedic surgery, gain hands-on experience in the design and development of novel machine learning-based predictive models, creating long-term networks, and creating a strong publication record. Feel free to reach out to learn more about the available positions and projects.

Bibliographic
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