About the University
Founded in 1923, Texas Tech University began with a mission to serve the needs of West Texas, but its impact has always reached far beyond. Today, Texas Tech, located in Lubbock (pop. 300,000+), is home to a vibrant community of more than 42,000 students.Texas Tech's 1,800-acre campus showcases Spanish Renaissance architecture and is home to one of the country's largest public art collections. Its 13 colleges include a prestigious School of Law and a distinguished School of Veterinary Medicine. These programs equip students with the skills and knowledge needed to excel in their respective fields. Built on the values of West Texas - hard work, grit and authenticity - the university graduates students who are deeply engaged in service to their communities and well-positioned to succeed in the world. Texas Tech is committed to achieving research and scholarly accomplishments that compare favorably to the member institutions of the Association of American Universities (AAU). For more than 100 years, Texas Tech has been a premier destination for those seeking a world-class education and a unique, personalized experience as a member of the Red Raider family.
About the Department and/or College
This position will be housed in the Human Molecular Aging Center and will work in collaboration with the department of Mathematics and Statistics.
The Human Molecular Aging Center (HMAC) is focused on advancing the understanding of molecular damage in brain aging. The center aims to create a comprehensive Human Molecular Atlas of Aging that spans multiple biological levels, including DNA, RNA, proteins, small molecules, organelles, and cells. The center will utilize cutting-edge analytical, biochemical, biophysical, and computational tools to explore molecular aging, with the goal of developing interventions to target the deleteriome and improve health span and longevity.
Major/Essential Functions
- Develop and implement computational statistical methods for analyzing largeâEUR'scale, heterogeneous, and multiâEUR'type datasets (e.g., continuous, categorical, functional, spatial, temporal, genomic, medical images).
- Design Bayesian models and inference algorithms, including hierarchical models, latent variable frameworks, and Bayesian computation (MCMC, variational inference, sequential Monte Carlo).
- Integrate multiâEUR'modal data sources using advanced statistical fusion techniques, joint modeling, and representation learning to extract coherent signals across disparate data types.
- Build and evaluate machine learning models-supervised, unsupervised, and semiâEUR'supervised-tailored to scientific or engineering applications requiring statistical rigor and interpretability.
- Develop scalable algorithms for highâEUR'performance computing environments, including parallelization, GPUâEUR'based computation, and optimization of statistical workflows.
- Quantify uncertainty in predictive models using Bayesian posterior analysis, bootstrap methods, and sensitivity analysis to ensure robust scientific conclusions.
- Collaborate with domain scientists to translate statistical ideas into actionable insights, ensuring methodological choices align with scientific objectives of HMAC.
- Develop reproducible research pipelines using software tools (e.g., Python, R, Stan, Matlab, PyMC, TensorFlow) and maintain high standards of documentation and code quality.
Required Qualifications
PhD in area of project specialization. Knowledge of modern research practices, the methods, resources, and standards thereof. Ability to organize work effectively, conceptualize and prioritize objectives and exercise independent judgment based on an understanding of organizational policies and activities. Ability to integrate resources, policies, and information for the determination of procedures, solutions and other outcomes. Ability to establish and maintain effective work relationships with other employees and the public. Ability to plan and allocate the workload of employees, providing direct training and supervision as needed.
Preferred Qualifications
Ph.D. in Mathematics or Statistics, grant writing experience, publication record
Pay Range
$48,000 - $63,700 - $78,400
