YUAN LAB - Postdoctoral Fellow - Myeloma Research
- The University of Texas M. D. Anderson Cancer Center
- Location: Houston, TX
- Job Number: 7126411
- Posting Date: Feb 23, 2023
- Application Deadline: Open Until Filled
Job Description
The research lab of Dr. Yinyin Yuan in the Department of Translational Molecular Pathology at UT MD Anderson Cancer Center is seeking a postdoctoral fellow. Our aim is to develop and integrate cutting edge artificial intelligence with digital pathology. Working closely with the Institute for Data Science in Oncology (IDSO) and the James P. Allison Institute, Dr. Yuan directs the computational pathology program that encompasses a large portfolio of innovative research using data and tissue samples collected in ongoing translational studies and immuno-oncology clinical trials. As the #1 cancer center in the U.S.A. and a leader in research and innovation, MDACC provides the ideal resources and environment for developing, testing, and deploying AI technologies for improved early cancer diagnosis and accurate treatment selection. The program is located in a newly constructed translational research space in the heart of the Texas Medical Center at the MDACC main campus in Houston, TX.
This research project aims to define the risk of smoldering myeloma for early detection of multiple myeloma. Multiple myeloma is an incurable plasma cell malignancy. Progression to multiple myeloma from its earlier disease state manifests as bone pain and fractures, kidney failure, infections, and the emergence of biologically aggressive treatment resistant states. Therefore, we must define new biomarkers to detect and predict malignant transformation early.
LEARNING OBJECTIVES
1. Develop AI-based image analysis models to detect single cell and tissue architectures
2. Identifying statistically significant microenvironmental features
3. Discovering outcome and genomic related pathology morphological biomarkers
The aim is to develop better markers and therapies to predict and ultimately prevent progression from a pre-cancer disease to incurable cancer. You will lead the development of new deep learning systems for analyzing digital pathological images of smoldering myeloma. You will enjoy the highly collaborative nature of this project, working with the internationally renowned team consisting of oncologists, pathologists, immunologists, and bioinformaticians at UCL, Broad Institute, Dana-Farber Cancer Institute, and others to deliver leading-edge toolkits to identify the genomic, transcriptomic and immunological landscape of smoldering myeloma.
ELIGIBILITY REQUIREMENTS
An individual holding a recent (within three years) Ph.D. in an appropriate field who is seeking a temporary appointment under the supervision of a faculty mentor involving full-time laboratory-based research or scholarship in preparation for an academic or research career as an independent investigator. This appointment is not part of a clinical training program; individuals holding an M.D. degree or equivalent are not permitted to engage in patient care activity.
ADDITIONAL APPLICATION INFORMATION
Translational Molecular Pathology Department website: (copy/past URL)
https://www.mdanderson.org/research/departments-labs-institutes/departments-divisions/translational-molecular-pathology.html
This research project aims to define the risk of smoldering myeloma for early detection of multiple myeloma. Multiple myeloma is an incurable plasma cell malignancy. Progression to multiple myeloma from its earlier disease state manifests as bone pain and fractures, kidney failure, infections, and the emergence of biologically aggressive treatment resistant states. Therefore, we must define new biomarkers to detect and predict malignant transformation early.
LEARNING OBJECTIVES
1. Develop AI-based image analysis models to detect single cell and tissue architectures
2. Identifying statistically significant microenvironmental features
3. Discovering outcome and genomic related pathology morphological biomarkers
The aim is to develop better markers and therapies to predict and ultimately prevent progression from a pre-cancer disease to incurable cancer. You will lead the development of new deep learning systems for analyzing digital pathological images of smoldering myeloma. You will enjoy the highly collaborative nature of this project, working with the internationally renowned team consisting of oncologists, pathologists, immunologists, and bioinformaticians at UCL, Broad Institute, Dana-Farber Cancer Institute, and others to deliver leading-edge toolkits to identify the genomic, transcriptomic and immunological landscape of smoldering myeloma.
ELIGIBILITY REQUIREMENTS
An individual holding a recent (within three years) Ph.D. in an appropriate field who is seeking a temporary appointment under the supervision of a faculty mentor involving full-time laboratory-based research or scholarship in preparation for an academic or research career as an independent investigator. This appointment is not part of a clinical training program; individuals holding an M.D. degree or equivalent are not permitted to engage in patient care activity.
ADDITIONAL APPLICATION INFORMATION
Translational Molecular Pathology Department website: (copy/past URL)
https://www.mdanderson.org/research/departments-labs-institutes/departments-divisions/translational-molecular-pathology.html
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html
