The Department of Bioengineering at The University of Texas at Arlington is seeking to analyze imaging data, develop novel methods for analysis and integration of multimodal neuroimaging, behavioral and clinical data, and build large-scale deep learning models for multimodal neuroimaging datasets to construct predictive network models in psychiatric disorders.
Requirements
- Ph.D 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.
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 dataset, brain imaging quality control and processing.
- Assist with grant applications, manuscript preparation and supervision of RAs and volunteers.
- Performs other duties as needed.
Other
- Ph.D degree in biomedical engineering, electrical engineering, computer science, biostatistics, or a related field.
- Excellent writing and communication skills.
- Strong interest in neuroscience and psychiatric research.
- Curriculum Vitae
- Cover Letter
