Summary

A Postdoctoral Associate - Specialist position in advanced computation is available in the Michael E. DeBakey Department of Surgery. This individual's training will focus on machine learning, AI, and other advanced approaches to create tools and analyze large clinical data sets under the guidance of the principal investigator. The ideal candidate must have a PhD in Computer Science or a related field, and have proficient programming skills, particularly in Python. Experience in large-scale machine learning modeling is also required.

The Postdoctoral Associate - Specialist will play a critical role in advancing cutting-edge research at the intersection of data science, machine learning, and surgical outcomes. This individual will receive training in data science using large clinical data sets under the guidance of the Principal Investigator (PI), and collaborate with a multidisciplinary team to conduct specialized research, develop innovative solutions, and contribute to high-impact scientific publications.

Job Duties

• Plans, directs, and executes specialized research projects related to surgical outcomes, leveraging data science techniques to address complex challenges.
• Designs and implements machine learning models, focusing on predictive algorithms for surgery-related outcomes. Continually refines and optimizes models to improve their accuracy and effectiveness.
• Develops and applies advanced statistical methodologies to analyze large-scale datasets, ensuring robust and reproducible results. Utilizes statistical software to interpret and visualize findings.
• Creates efficient data pipelines and digital frameworks for the consumption, organization, validation, storage, and classification of electronic health data
• Ensures compliance with data privacy and security standards.
• Coordinates and oversees data collection processes using various methodologies, such as surveys, focus groups, and direct patient data extraction. Ensures high-quality and representative data for research.
• Prototypes, troubleshoots, and fine-tunes machine learning models for outcome predictions relevant to surgery. Evaluates model performance using key metrics like precision-recall, receiver operating characteristic curves, and confusion matrices.
• Designs, trains, and evaluates neural networks, particularly for computer vision tasks such as object detection and image classification, relevant to surgery-related applications.
• Develops and maintains software packages for prototype systems that are utilized in the analysis and prediction of surgical outcomes. Ensures that software tools are well-documented and scalable.
• Communicates research findings effectively by presenting at lab meetings, as well as at national and international conferences. Prepares clear and comprehensive visualizations and reports to support data-driven insights.
• Assists the PI in the preparation of grant proposals by contributing to the development of research plans for securing funding from external agencies.
• Leads or contributes to the writing of scientific manuscripts for peer-reviewed journals, detailing findings from research projects and innovations in data science as applied to surgery.

Minimum Qualifications

• Ph.D. in Chemistry, Computational Sciences, Computational Biology, Structural Biology, Computer Science, Bioinformatics, Statistics, or related disciplines. May also include Ph.D. in Biology or Biomedical Sciences in combination with an M.S. or extensive multidisciplinary experience in one of the above quantitative fields.

Preferred Qualifications

• Proficiency in machine learning, statistical analysis, and experience with tools such as Python, R, TensorFlow, and PyTorch.
• Strong background in analyzing large-scale healthcare datasets, and familiarity with electronic health records is a plus.