Post Doctoral Research Associate
The University of Texas at Arlington, Arlington, TX, United States
Job Summary
The Department of Bioengineering in the College of Engineering at the University of Texas at Arlington invites applications for a rank Post Doctoral Research Associate. This position will focus on analyzing imaging data, developing novel methods for analysis and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in psychiatric disorders.
Required Qualifications
PhD degree in biomedical engineering, electrical engineering, computer science, biostatistics or a related field
Preferred Qualifications
Doctor degree in biomedical engineering, electrical engineering, computer science, biostatistics or a related field
Experience in working with an MRI scanner
Experience in developing state-of-the-art Machine Learning algorithms
Experience with one or more deep learning libraries such as PyTorch, TensorFlow, or Keras
Hands‑on experience with neuroimaging processing pipelines
Excellent writing and communication skills
Strong interest in neuroscience and psychiatric research
Essential Duties And Responsibilities
Neuroimaging data collection and management
Data analysis and model building
Develop advanced deep learning and machine learning algorithms
Assist with organizing large-scale multimodal neuroimaging datasets, brain imaging quality control, and processing
Assist with grant applications, manuscript preparation, and supervision of RAs and volunteers
Performs other duties as needed
#J-18808-Ljbffr
The Department of Bioengineering in the College of Engineering at the University of Texas at Arlington invites applications for a rank Post Doctoral Research Associate. This position will focus on analyzing imaging data, developing novel methods for analysis and integration of multimodal neuroimaging, behavioral and clinical data, and building large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in psychiatric disorders.
Required Qualifications
PhD degree in biomedical engineering, electrical engineering, computer science, biostatistics or a related field
Preferred Qualifications
Doctor degree in biomedical engineering, electrical engineering, computer science, biostatistics or a related field
Experience in working with an MRI scanner
Experience in developing state-of-the-art Machine Learning algorithms
Experience with one or more deep learning libraries such as PyTorch, TensorFlow, or Keras
Hands‑on experience with neuroimaging processing pipelines
Excellent writing and communication skills
Strong interest in neuroscience and psychiatric research
Essential Duties And Responsibilities
Neuroimaging data collection and management
Data analysis and model building
Develop advanced deep learning and machine learning algorithms
Assist with organizing large-scale multimodal neuroimaging datasets, brain imaging quality control, and processing
Assist with grant applications, manuscript preparation, and supervision of RAs and volunteers
Performs other duties as needed
#J-18808-Ljbffr