This Research Fellow position focuses on developing and applying advanced artificial intelligence and machine learning methods within clinical settings. Working under the mentorship of a principal investigator, the fellow will contribute to research in AI and informatics, particularly in clinical imaging and data analysis. The role involves designing, implementing, and evaluating computational models while collaborating with interdisciplinary teams to translate research into real-world healthcare applications. This position is designed as a training opportunity to build research expertise, support publication efforts, and prepare candidates for future research funding and academic advancement.

Responsibilities:

• Develop and validate AI and machine learning models for clinical applications
• Analyze and process imaging and multimodal clinical data
• Design and implement computational and statistical models
• Collaborate with clinical teams to translate research into practice
• Support deployment of models into clinical environments
• Conduct experimental design and statistical evaluation
• Publish research findings in academic journals and conferences
• Work independently and within multidisciplinary teams

Qualifications:

• PhD in Computer Science, Engineering, Biomedical Engineering, Applied Mathematics, Medical Physics, or related field
• Strong background in AI and machine learning for clinical imaging
• Experience with image processing, data analysis, and modeling techniques
• Proficiency in Python and machine learning frameworks such as TensorFlow or PyTorch
• Experience with generative models such as GANs, diffusion models, or large language models
• Knowledge of multi-modal data integration including imaging, clinical data, or genomics
• Strong communication skills and publication record

Preferred Qualifications:

• Experience with scalable computing or distributed systems
• Experience with MLOps or research deployment pipelines
• Knowledge of clinical imaging physics or computational biology

Additional Information:

Full-time position with standard Monday through Friday schedule

Training-focused research role with mentorship

Opportunity for publication and academic advancement

Pay Type: Salary

Compensation: $71,992.20 – $84,220.50 per year

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