Job Description:
We seek a postdoctoral fellow for a project that aims to quantitatively extract structural and functional cancer imaging features from clinical trial imaging data sets (MRI, PET-CT and CT). This process will utilize a high-throughput image characterization workflow, with correspondence assessed among selected imaging features, genomic signatures, and molecular markers to ultimately improve patient stratification and outcome measures. A combination of automated and manual image characterization methods will be used to determine suitable quantitative imaging biomarkers, as part of a precision-based radiomics effort. Additional goals will be to develop and evaluate novel computational imaging processing tools, as well as predictive and prognostic models, on the basis of existing and future patient cohorts from clinical oncology trials conducted at Memorial Sloan Kettering Cancer Center. This position will allow for collaborative interactions with other relevant areas, including imaging, image analysis, bioinformatics, computational biology, and machine learning. Candidates are required to have a doctorate in Engineering, Physics, Computer Science, Physics, Bioinformatics, or related subjects with expertise in the application of advanced imaging analysis techniques. Hands-on experience in high performance computing, such as R, C/C++ and Unix / Matlab programming environments, as well as experience with imaging modalities (CT, MRI, PET), including image acquisition and reconstruction protocols and standardization is desirable. An understanding of health information technology systems (vendor neutral archive, DICOM) would also be helpful.
Additional Info:
Location: New York City, New York (US) Salary: Compensation based on work experience Employer: bradburm@mskcc.org[Click Here to Access the Original Job Post]
We seek a postdoctoral fellow for a project that aims to quantitatively extract structural and functional cancer imaging features from clinical trial imaging data sets (MRI, PET-CT and CT). This process will utilize a high-throughput image characterization workflow, with correspondence assessed among selected imaging features, genomic signatures, and molecular markers to ultimately improve patient stratification and outcome measures. A combination of automated and manual image characterization methods will be used to determine suitable quantitative imaging biomarkers, as part of a precision-based radiomics effort. Additional goals will be to develop and evaluate novel computational imaging processing tools, as well as predictive and prognostic models, on the basis of existing and future patient cohorts from clinical oncology trials conducted at Memorial Sloan Kettering Cancer Center. This position will allow for collaborative interactions with other relevant areas, including imaging, image analysis, bioinformatics, computational biology, and machine learning. Candidates are required to have a doctorate in Engineering, Physics, Computer Science, Physics, Bioinformatics, or related subjects with expertise in the application of advanced imaging analysis techniques. Hands-on experience in high performance computing, such as R, C/C++ and Unix / Matlab programming environments, as well as experience with imaging modalities (CT, MRI, PET), including image acquisition and reconstruction protocols and standardization is desirable. An understanding of health information technology systems (vendor neutral archive, DICOM) would also be helpful.
Requeriments :
Skills :
- Biomarker Discovery
- HPC
- Lunix/Unix
- Programing in C
- Programing in C++
- Programming in Matlab
- Programming in R
Areas :
Additional Info:
Location: New York City, New York (US) Salary: Compensation based on work experience Employer: bradburm@mskcc.org[Click Here to Access the Original Job Post]