Job Description
Summary
The Department of Radiology at BCM seeks a highly motivated and talented Postdoctoral Associate for the Translational Imaging Group at the forefront of machine learning and artificial intelligence in research and clinical imaging. The successful candidate will contribute to cutting-edge research projects that aim to develop and apply AI/machine learning algorithms to improve the accuracy, efficiency, and clinical utility of radiological diagnosis and predict future health trajectories.
The Translational Imaging Group (TIGr) offers an excellent training environment for Postdoctoral Associates. TIGr is a diverse and collaborative team composed of engineers, clinicians, biologists, and mathematicians at all career stages, from early career scientists and graduate students to seasoned researchers with over 30 years of experience. Our group focuses on developing the next generation of medical imaging technologies by designing, building, and testing innovative imaging methods, devices, and materials. Our current research includes exploring novel nanoparticle contrast agents for CT and MRI, developing next-generation molecular imaging agents, advancing near-infrared imaging devices for deep-tissue optical imaging, creating novel imaging agents and methods for low-field permanent magnet MRI, and developing novel risk analytics based on deep learning and machine learning dedicated to pediatric population clinical needs.
Job Duties
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Designs, develops, and implementsinnovative machine learning and deep learning algorithms to analyze medical images like CT scans, MRIs, and PET scans.
- Successful candidate will research various applications, including image segmentation, classification, object detection, and image reconstruction.
- Collaborateswith radiologists and clinicians is essential to identify critical clinical needs and ensure that research findings are translated effectively into clinical practice.
- Preparesand analyzeslarge-scale medical imaging datasets and evaluatesthe performance of the algorithms you develop.
- Publishesresearch findings in peer-reviewed journals and present at scientific conferences.
- Contributes to grant proposal writing and research project management.
- Mentors and trains junior researchers and students.
Minimum Qualifications
- MD or Ph.D. in Basic Science, Health Science, or a related field.
- No experience required.
Preferred Qualifications
- Ph.D. in Computer Science, Biomedical Engineering, or a related field.
- Strong background in machine learning, deep learning, and computer vision.
- Proficiency in programming languages such as Python and relevant deep learning frameworks (e.g., TensorFlow, PyTorch).
- Excellent analytical, problem-solving, and communication skills.
- Ability to work independently and as part of a multidisciplinary team.
- Experience with medical image analysis and processing.
- Familiarity with medical imaging modalities and radiology workflows.
- Experience with cloud computing platforms (e.g., AWS, Google Cloud).
- Knowledge of human and rodent anatomy, image registration, segmentation.
- Contributions to open-source projects or scientific publications in relevant fields.
Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.
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Baylor College of Medicine fosters diversity among its students, trainees, faculty and staff as a prerequisite to accomplishing our institutional mission, and setting standards for excellence in training healthcare providers and biomedical scientists, promoting scientific innovation, and providing patient-centered care. - Diversity, respect, and inclusiveness create an environment that is conducive to academic excellence, and strengthens our institution by increasing talent, encouraging creativity, and ensuring a broader perspective. - Diversity helps position Baylor to reduce disparities in health and healthcare access and to better address the needs of the community we serve. - Baylor is committed to recruiting and retaining outstanding students, trainees, faculty and staff from diverse backgrounds by providing a welcoming, supportive learning environment for all members of the Baylor community.