Summary

A Postdoctoral Associate position is available in the Michael E. DeBakey Department of Surgery. The postdoctoral associate will be responsible for developing machine learning algorithms and creating predictive models. This role will contribute to evidence-based processes and procedures for program quality review and assessment of outcomes data as well as develop analytical methods and digital capability for data consumption, organization, validation, storage, and classification of electronic health data.

Job Duties

• Develops analytical methods and digital capability for data consumption, organization, validation, storage, and classification of electronic health data.
• Provides data management support to faculty.
• Facilitates data collection through surveys, focus groups, and other methods.
• Collects data using cameras, sensors, and data acquisition systems.
• Prototypes, troubleshoots, and fine-tunes machine learning models for outcome predictions relevant to surgery.
• Evaluates machine learning training using tools such as precision-recall metrics, receiver-operating characteristics curves, and confusion matrices.
• Trains and evaluates neural networks for computer vision tasks, such as object detection.
• Contributes to evidence-based processes and procedures for program quality review and assessment of outcomes data. • Build software packages for prototype systems. 

Minimum Qualifications

• MD or Ph.D. in Basic Science, Health Science, or a related field.
• No experience required.

Preferred Qualifications

• Proficiency in Python, MATLAB, and R, combined with experience in signal and image analysis, as well as familiarity with electronic health data, will be distinct advantages.
• Experience in large-scale machine learning modeling is also required.
• Strong writing and communication skills with excellent interpersonal skills.