Postdoctoral Fellow - Radiation Physics (Zhang Lab)
- Requisition #: 600662-202407221417
- Department: Radiation Physics - Research
- Location: Houston, TX
- Posted Date: 7/22/2024
The MD Anderson Proton Therapy Center seeks a highly motivated postdoctoral fellow to join our team and conduct cancer-related research at the University of Texas MD Anderson Cancer Center. This position will focus on NIH-funded basic research to enhance patient survival rates using advanced pathology and radiology imaging for various types of cancer.
The Postdoctoral Fellow will analyze and process radiation and pathology images; develop and translate state-of-the-art Deep Learning/Machine Learning methods into real clinical applications; improve and accelerate existing DL/ML methods on High-Performance Computer systems; and develop and enhance computational tools. The candidate is expected to work independently on advancing tumor registration, segmentation, dose distribution prediction, automated treatment planning, and other tasks.
LEARNING OBJECTIVES
The trainee will learn to utilize innovative DL/ML approaches in cancer systems radiology and pathology to develop translational tools for cancer systems research. This includes accurate tumor segmentation, predicting dose distribution, automated treatment planning, and evaluating cancer status, ultimately aiming to improve the survival rate of cancer patients.
ELIGIBILITY REQUIREMENTS
1. Ph.D. Degree in Computer Science or related field focusing on data analysis, information science, high-performance computing, computer vision, machine learning, or artificial intelligence.
2. Strong background in computer vision, machine learning, data cleaning, data analysis, data processing, or HPC systems.
3. Demonstrated experience driving research in and applying Computer Vision techniques (e.g., Transformers, CNNs, RNNs, GANs) is required.
4. Proven expertise in modern image analysis techniques (e.g., foundation models, transformers, self-supervised learning) is required.
5. Hands-on experience in ML techniques, algorithms, off-the-shelf packages such as OpenCV, SciKit-Learn, and Pytorch, and development environments (Liunx).
6. Experience with large-scale dataset collection, annotation, and curation.
7. Experience with HPC systems.
8. Background in natural language processing.
9. Strong written and oral communication skills, including developing and delivering presentations, proposals, and technical documents.
10. Strong ability to work both independently and in a team environment.
POSITION INFORMATION
MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000. depending on the number of years of postgraduate experience. MD Anderson trainee compensation also includes:
-Paid medical benefits (zero premium) starting on the first day for trainees who work 30 or more hours per week
-Group dental, vision, life, AD&D, and disability coverage
-Paid education, vacation, and sick leave
-Paid institutional holidays, wellness leave, childcare leave, and other paid leave programs
-Teachers Retirement System defined-benefit pension plan and two voluntary retirement plans
-Employer-paid life, AD&D, and an illness-related reduced salary pay program
-Health Savings Account and Dependent Care Reimbursement flexible spending accounts
-Fertility benefits
-State of Texas longevity pay
-Extensive wellness, fitness, employee health programs, and employee resource groups
The Postdoctoral Fellow will analyze and process radiation and pathology images; develop and translate state-of-the-art Deep Learning/Machine Learning methods into real clinical applications; improve and accelerate existing DL/ML methods on High-Performance Computer systems; and develop and enhance computational tools. The candidate is expected to work independently on advancing tumor registration, segmentation, dose distribution prediction, automated treatment planning, and other tasks.
LEARNING OBJECTIVES
The trainee will learn to utilize innovative DL/ML approaches in cancer systems radiology and pathology to develop translational tools for cancer systems research. This includes accurate tumor segmentation, predicting dose distribution, automated treatment planning, and evaluating cancer status, ultimately aiming to improve the survival rate of cancer patients.
ELIGIBILITY REQUIREMENTS
1. Ph.D. Degree in Computer Science or related field focusing on data analysis, information science, high-performance computing, computer vision, machine learning, or artificial intelligence.
2. Strong background in computer vision, machine learning, data cleaning, data analysis, data processing, or HPC systems.
3. Demonstrated experience driving research in and applying Computer Vision techniques (e.g., Transformers, CNNs, RNNs, GANs) is required.
4. Proven expertise in modern image analysis techniques (e.g., foundation models, transformers, self-supervised learning) is required.
5. Hands-on experience in ML techniques, algorithms, off-the-shelf packages such as OpenCV, SciKit-Learn, and Pytorch, and development environments (Liunx).
6. Experience with large-scale dataset collection, annotation, and curation.
7. Experience with HPC systems.
8. Background in natural language processing.
9. Strong written and oral communication skills, including developing and delivering presentations, proposals, and technical documents.
10. Strong ability to work both independently and in a team environment.
POSITION INFORMATION
MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000. depending on the number of years of postgraduate experience. MD Anderson trainee compensation also includes:
-Paid medical benefits (zero premium) starting on the first day for trainees who work 30 or more hours per week
-Group dental, vision, life, AD&D, and disability coverage
-Paid education, vacation, and sick leave
-Paid institutional holidays, wellness leave, childcare leave, and other paid leave programs
-Teachers Retirement System defined-benefit pension plan and two voluntary retirement plans
-Employer-paid life, AD&D, and an illness-related reduced salary pay program
-Health Savings Account and Dependent Care Reimbursement flexible spending accounts
-Fertility benefits
-State of Texas longevity pay
-Extensive wellness, fitness, employee health programs, and employee resource groups
FACULTY MENTOR
Xiaodong Zhang, Ph.D.
