The Vice Chair for Clinical Machine Learning (VC - CML) develops and operationalizes Moffitt’s strategic roadmap for the utilization of Artificial Intelligence/Machine Learning (AI/ML) in clinical settings, including the assessment and prioritization of commercial products and research prototypes of developed machine learning algorithms for oncology (e.g., EHR, radiology, pathology, clinical trials, or radiation oncology). The VC-CML also assists the Chair of Machine Learning with academic leadership activities (e.g., recruitment, mentoring, retention, budgeting, strategic planning)
Requirements:
PhD and/or MD with expertise in the application of AI/ML to clinical workflows and processes; Technical AI/ML knowledge and skills ideally obtained through formal training in AI and ML, with demonstrated track record in the field; Experience optimizing clinical workflow and/or implementing clinical decision support tools that leverage AI/ML; documented examples of significant work in this area is preferred; Excellent interpersonal communication skills; ability to build team consensus with diverse groups of stakeholders; leads through positive influence; Experience obtaining NIH-grants funding as an independent PI
Text:
Tenure-Earning Vice Chair for Clinical Machine Learning The Vice Chair for Clinical Machine Learning (VC - CML) develops and operationalizes Moffitt’s strategic roadmap for the utilization of Artificial Intelligence/Machine Learning (AI/ML) in clinical settings, including the assessment and prioritization of commercial products and research prototypes of developed machine learning algorithms for oncology (e.g., EHR, radiology, pathology, clinical trials, or radiation oncology). The VC-CML also assists the Chair of Machine Learning with academic leadership activities (e.g., recruitment, mentoring, retention, budgeting, strategic planning) PhD and/or MD with expertise in the application of AI/ML to clinical workflows and processes; Technical AI/ML knowledge and skills ideally obtained through formal training in AI and ML, with demonstrated track record in the field; Experience optimizing clinical workflow and/or implementing clinical decision support tools that leverage AI/ML; documented examples of significant work in this area is preferred; Excellent interpersonal communication skills; ability to build team consensus with diverse groups of stakeholders; leads through positive influence; Experience obtaining NIH-grants funding as an independent PI
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