Summary

The Office of Surgical Research (OSR) within the Michael E. DeBakey Department of Surgery is seeking a Staff Scientist to develop advanced analytic tools (data mining, machine learning, and artificial intelligence) for research projects using surgical data. The Staff Scientist will collaborate with research faculty and other research personnel to design and conduct research experiments using machine learning algorithms and creating predictive models.  The ideal candidate must demonstrate a robust background in data science and machine learning, encompassing the application of statistical methods, the creation of predictive models, and the development of machine learning algorithms. 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.

Job Duties

• Plan, direct, and conduct research projects related to surgical data.
• Collect, clean, and preprocess structured and unstructured data from various sources to build high-quality datasets for analysis.
• Analyze large amounts of data to find patterns and solutions.
• Develop prediction systems and machine learning algorithms to select features, create and optimize classifiers.
• Design and conduct experiments to validate findings.
• Prototype, troubleshoot, and fine-tune machine learning models for outcome predictions relevant to surgery.
• Evaluate machine learning training using tools such as precision-recall metrics, receiver-operator curves, and confusion matrices.
• Present data to investigators.
• Author scientific manuscripts.

Minimum Qualifications

• Doctoral Degree. Experience may not be substituted in lieu of degree.
• Three years of post doctoral research experience.

Department Specific Criteria

• Background in data science and machine learning, encompassing the application of statistical methods, the creation of predictive models, and the development of machine learning algorithms.
• Proficiency in Python, MATLAB, and R, combined with experience in image analysis.
• Familiarity with electronic health data.