**Job Description**
This Postdoctoral Associate position in the Department of Radiology involves investigating generative models, with a focus on their applications to next-generation MR image reconstruction. The role includes training deep neural networks, performing quantitative data analysis, and collecting and analyzing data through literature search and specialized skills. Responsibilities extend to participating in manuscript writing for publications, assisting with grant applications, and performing lab maintenance. The successful candidate will join the AMRIS Lab, possessing strong communication and problem-solving skills, and a willingness to mentor junior lab members, with a particular interest in applying reinforcement learning to MRI systems.
**Skills & Abilities**
• Proficiency in Python, C/C++, and Unix-like operating systems (Preferred)
• Good verbal and written communication skills in English
• Ability to work productively and independently in a collaborative environment
• Strong problem-solving skills
• Willingness to provide mentorship to junior lab members
**Qualifications**
Required Degree(s) in:
• Electrical and Computer Engineering
• Computational Science
• Mathematics
• Physics
• Closely related field
Other:
• Doctoral Degree (or foreign equivalent)
• Proficiency in machine learning libraries (e.g., scikit-learn, PyTorch, transformers) and data analysis tools (e.g., pandas, NumPy, CuPy)
• Hands-on experience in training large neural networks (generative models)
• Hands-on experience in medical image reconstruction
• Background in MRI physics (Preferred)
**Experience**
Other:
• Hands-on experience in training large neural networks (generative models)
• Hands-on experience in medical image reconstruction
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