RECENT FACULTY AWARDED GRANTS
Professor Peng Wei was awarded a grant from the Cancer Prevention and Research Institute of Texas (CPRIT) in support of cancer research, titled: Integrative modeling of spatially resolved multi-omics data to identify bladder cancer mucosal field effects.
Professors Ying Yuan and Liang Li are Co-PIs and Assistant Professor Ziyi Li Co-I on an NCI U24 grant for a Coordinating and Data Management Center (CDMC) for the Translational and Basic Science Research in Early Lesions (TBEL) Program. This program aims to integrate basic and translational cancer research studies to understand biological precancer and early cancer drivers/restraints and facilitate biology-based precision prevention approaches. This new grant expands the ongoing NIH-funded CDMC for the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer, also managed by Drs. Yuan and Li.
Assistant Professor Ziyi Li is PI on an R03 award from NIH/NCI (1R03CA270725) titled Statistical Models for Intratumor Heterogeneity of Tumor-infiltrated Leukocytes in Lung Cancer.
Associate Professor Jing Ning and Department Chair ad interim and Conversation with a Living Legend Professor Yu Shen (MPI) were awarded an R01 grant from NCI (CA269696-01) titled Statistical Methods for Integration of Multiple Data Sources toward Precision Cancer Medicine.
Assistant Professor Christine Peterson is PI for the NIH/NHLBI R01 grant titled New Data Science Approaches to Visualize and Understand the Impact of the Microbiome on Risk of Graft-versus-host Disease.
Associate Professor Suyu Liu received an R01 grant (2R01CA160254-10) subaward via the University of Michigan titled Serum Glyco-Markers of Early Hepatocellular Carcinoma Using a Mass Spec Approach, for which she is PI.
Professor Peter Thall and Assistant Professor Ruitao Lin (MPI) were awarded an R01 grant (1R01CA261978-01) titled Bayesian Methods for Complex Precision Biotherapy Trials in Oncology.
Professor Liang Li received a CPRIT grant for Data Management and Analysis Core for Comparative Effectiveness Research on Cancer in Texas, for which he is Co-PI.
Assistant Professor Christine Peterson received the National Science Foundation Division of Mathematical Sciences DMS- 2113602 and DMS- 2113557 grants for Collaborative Research: Covariate-driven Approaches to Network Estimation, for which she is Co-PI.
Professor J. Jack Lee will serve as the Core Director for The University of Texas MD Anderson Cancer Center SPORE in Melanoma, Core 3 Biostatistics and Bioinformatics. The goal is to provide comprehensive service to guide experiment design to optimize quantitative data analysis, while maintaining statistical justification and results interpretation through sound experimental design principles tailored to each project. This will include data analyses and contributions to the interpretation of results via written reports and interactions with investigators.
MD ANDERSON BIOSTATISTICS AT ENAR 2023
Faculty, analysts, postdoctoral fellows, and graduate researchers from the Biostatistics department organized sessions, gave presentations, and/or had coauthored work presented at the ENAR 2023 Spring Meeting, March 19-22, 2023.
ENAR Invited Sessions
Evan Kwiatkowski, A Benchmark Effective Sample Size to Measure Information Borrowing in Hybrid Designs; J Jack Lee (chair), In Remembrance and Honor of Dr. Edmund Gehan – A Pioneer Biostatistician, Trail Blazer, and Mentor; Yisheng Li, A Semi-Mechanistic Dose-Finding Design in Oncology Using Pharmacokinetic/Pharmacodynamic Modeling; Ziyi Li, Accurate Identification of Locally Aneuploid Cells by Incorporating Cytogenetics Information in Single Cell Data Analysis; Ziyi Li (chair), Recent Advances in Precision Medicine with High-dimensional Biomedical Data; Ruitao Lin, Bayesian Predictive Platform Design for Proof of Concept and Dose Finding; Xuetao Lu, Distillation Decision Tree; Jing Ning, Combining Primary Cohort Data with External Aggregate Information without Assuming Comparability; Alec Reinhardt, Bayesian Longitudinal Tensor Response Regression for Modeling Neuroplasticity; Yi Yao, Dynamic Prediction Using Backward Joint Model with Multivariate Nonlinear Longitudinal Biomarker Trajectories; Ying Yuan, Elastic Priors to Dynamically Borrow Information from Historical Data in Clinical Trials; Feng Zhang, Meta-Analysis for Modeling Studies with Multiple Cut-Points and a Simulation Study; Jinhao Zou, Approaches to Estimate Bidirectional Causal Effects Using Mendelian Randomization.
Licai Huang, Joint Bayesian Additive Regression Tree Model for Flexible Prediction from Genomic Data; Srijata Samanta, Consistent Bayesian Variable Selection in High-Dimensional Hierarchical Regression; Peng Yang, A Novel Bayesian model for Assessing Intratumor Heterogeneity of Tumor Infiltrating Leukocytes with MultiRegion Gene Expression Sequencing; Yan Li, Propensity Score Analysis with Local Balance; Chao Yang, An Extended Bayesian Semi-Mechanistic Dose-Finding Design for Phase I Oncology Trials Using Pharmacokinetic and Pharmacodynamic Information
Yan Li, Latent Variables
MD ANDERSON BIOSTATISTICS AT JSM 2022
Faculty, analysts, postdoctoral fellows and graduate researchers from the Biostatistics department organized sessions, gave presentations, and/or had coauthored work presented at the JSM 2022 conference, August 6-11, 2022.
JSM Invited Sessions
Christine Peterson, Bayesian Sparse Modeling to Identify High-Risk Subgroups; Kim Anh-Do, Scalnet: Scalable Network Estimation with L0 Penalty; Suprateek Kundu, Statistical Approaches for Integrative Learning for Neuroimaging Data; Yu Shen, Jing Ning, Cautionary Tales of 'Old' RCT Evidence in 'New' Era.
JSM Contributed Sessions
Ziqiao Wang, Peng Wei, Spatial IMIX: A Mixture Model Approach to Spatially Correlated Multi-Omics Data Integration; Ziyi Li, Yizhuo Wang, Kim Anh-Do, Identifying Novel Cells in Annotating Single Cell RNA-Seq Data; Ruitao Lin, Peter Thall, Ying Yuan, BAGS: A Bayesian Adaptive Group Sequential Trial Design with Subgroup-Specific Survival Comparisons, A Bayesian Predictive Platform Design for Proof of Concept and Dose-Finding Using Early and Late Endpoints; Ying Yuan, Ruitao Lin, Bayesian Empirical Balancing Calibration for Addressing Nonconcurrent Controls in Adaptive Platform Trials; Ruitao Lin, BOREC: A Bayesian Optimal Design for Randomized Dose Expansion Cohorts in Oncology Trials, BOB: Bayesian Optimal Design for Biosimilar Trials with Co-Primary Endpoints; Ziyi Li, NeuCA: A Neural Network-Based Cell Annotation Method with Web-App and GUI, Incorporating Cell-Type Hierarchy Improves Cell-Type Specific Differential Analyses in Bulk Omics Data; Suyu Liu, Peter Thall, Ying Yuan, Group-Sequential Enrichment Designs Based on Adaptive Regression of Response and Survival Time on High-Dimensional Covariates; Ying Yuan, Recent Development in Bayesian Dynamic Borrowing with Application to Clinical Trials (contributed panel); BPAD: A Bayesian Basket Design for Pediatric Trials with Adult Data; Suyu Liu, Ying Yuan, A Bayesian Group Sequential Enrichment Design with Adaptive Regression of Response and Survival Time on Baseline Biomarkers; Peng Wei, Sunyi Chi, Zhichao Xu, Bin Shi, Xuelin Huang, R2-Based Mediation Analysis with High-Dimensional Omics Mediators; Sunyi Chi, Xuelin Huang, Peng Wei, MASH: Mediation Analysis of Survival Outcome and High-Dimensional Omics Mediators with Application to Complex Diseases; Xuelin Huang, A Flexible-Hazards Cure Model with Application to Patients with Soft Tissue Sarcoma; Peng Wei, Predicting Outcomes of Phase III Oncology Trials with Bayesian Mediation Modeling of Tumor Response; Peter Thall, Suyu Liu, Ying Yuan, A Bayesian Group Sequential Enrichment Design with Adaptive Regression of Response and Survival Time on Baseline Biomarkers; Ryan Sun, Inference for Set-Based Effects in Genome Wide Association Studies with Multiple Interval-Censored Outcomes; Jing Ning, Evaluating Dynamic Discrimination Performance of Risk Prediction Models for Survival Outcomes’, Semiparametric Isotonic Regression Analysis for Risk Assessment Under Nested Case-Control and Case-Cohort Designs, Bayesian Estimation of a Joint Semiparametric Recurrent Event Model of Multiple Cancer Types with Applications to the Li-Fraumeni Syndrome
JSM Posters / Speed Sessions
Liang Li, Tackling Dynamic Prediction of Death in Patients with Recurrent Cardiovascular Events.
Ning elected ASA Fellow
Jing Ning, Ph.D., was elected as a fellow of the American Statistical Association (ASA) in April, 2022. This honor recognizes her outstanding contributions to the profession of statistics and as a member of ASA.
Wei elected ASA Fellow
Peng Wei, Ph.D., was elected as a fellow of the American Statistical Association (ASA) in April, 2022. This honor recognizes his outstanding contributions as a member and to the profession of statistics.
Li elected AAAS Fellow
Liang Li, Ph.D., was elected as a fellow in the American Association for the Advancement of Science (AAAS). This honor recognizes invaluable contributions to science and technology via a process of peer selection since 1874.
Lee elected AAAS Fellow
J. Jack Lee, Ph.D., was elected as a fellow in the American Association for the Advancement of Science (AAAS). A process of selection by peers in the organization since 1874, this honor recognizes invaluable contributions to science and technology.
Two biostatistics faculty are Fellows of the Society for Clinical Trials
Professors Peter F. Thall (2014) and J. Jack Lee (2017) are Fellows of the Society for Clinical Trials. This fellowship honors society members who have made significant contributions to the advancement of clinical trials and to the society.
Eight biostatistics faculty are ASA fellows
Nine of the department's faculty members have attained the prestigious honor of being named a Fellow in the American Statistical Association: Donald A. Berry (1986), Kim-Anh Do (2006), Yu Shen (2007), J. Jack Lee (2008), Sanjay Shete (2012), Peter F. Thall (2015), Xuelin Huang (2017), Ying Yuan (2017), and Peng Wei (2022).
Multiple open rank non-tenure track research faculty positions at The University of Texas MD Anderson Cancer Center
The University of Texas MD Anderson Cancer Center is a comprehensive cancer center in Houston, Texas. It is the largest cancer center in the US and one of the original three comprehensive cancer centers in the country. It is both a degree-granting academic institution and a cancer treatment and research center located at the Texas Medical Center in Houston. It is ranked number 1 for cancer care in U.S. News & World Report’s “Best Hospitals” survey. Researchers at MD Anderson are empowered to conduct cross-disciplinary, collaborative science to accelerate discovery, including implementing transformative approaches that yield radical innovation. The institution invested more than $900 million in research last year, and it has made significant investments for the future.
We seek candidates to join the Department of Biostatistics at MD Anderson. Candidates with statistical expertise in the application of broad biomedical sciences are expected to conduct collaborative research in biostatistics and medical sciences, to obtain external funding, and to provide biostatistics education. Responsibilities include collaboration with clinical and basic science departments, statistical methodology research, teaching and mentoring graduate students. Applicants should demonstrate prowess in interdisciplinary, collaborative scientific research. A Ph.D. in statistics, biostatistics, or a related quantitative field is required.
Application should be emailed to: email@example.com. Please include: (a) cover letter, (b) CV, (c) Research statement (maximum 3 pages), and (d) contact information of individuals who will provide recommendation letters. There is no deadline to apply, and applications are reviewed on a rolling basis. (Posted December 15, 2022)
Multiple open rank tenure-track/tenured faculty positions at The University of Texas MD Anderson Cancer Center
The University of Texas MD Anderson Cancer Center is a comprehensive cancer center in Houston, Texas. It is the largest cancer center in the US and one of the original three comprehensive cancer centers in the country. It is both a degree-granting academic institution and a cancer treatment and research center located at the Texas Medical Center. MD Anderson is ranked No. 1 for cancer care in U.S. News & World Report’s “Best Hospitals” survey. Researchers at the institution are empowered to conduct cross-disciplinary, collaborative science to accelerate discovery, including implementing transformative approaches that yield radical innovation. MD Anderson invested more than $900 million in research last year, and it has made significant investments for the future.
MD Anderson Cancer Center has several incredible opportunities for multiple tenure-track/tenured open rank (assistant/associate/full) professors to direct cutting-edge basic, translational, clinical, population, or data science research programs. We seek candidates to join the Department of Biostatistics at MD Anderson in advancing methodology research in biostatistics and data science, making discoveries to improve health, and providing an innovative biostatistics education. Responsibilities include methodological and collaborative research, teaching, and mentoring graduate students. Applicants should demonstrate independent research with a publication record, the ability/potential to obtain external funding as principal investigator, and prowess in interdisciplinary, collaborative scientific research. The department will consider candidates who develop statistical methods with application to biomedical research. A Ph.D. in statistics, biostatistics, or a related quantitative field is required.
Applications should be emailed to: firstname.lastname@example.org. Please include: (a) cover letter, (b) CV, (c) research statement (maximum three pages), (d) three full-length research papers, and (e) contact information of individuals who will provide recommendation letters. There is no deadline to apply, and applications are reviewed on a rolling basis.
Contact Email for questions: email@example.com
(Posted on December 15, 2022)
Join the team that is once again number one in cancer care at The University of Texas MD Anderson Cancer Center, Department of Biostatistics. Ranked by U.S. News and World Report’s annual “Best Hospitals” survey, the institution has held the top two positions since the start of the list. From Nobel-level collaborations to programs that dramatically accelerate the conversion of scientific discovery into clinical realities, your work will help make cancer history.
Exceptional candidates are sought for multiple tenured/tenure-track faculty positions at the Assistant, Associate, or full Professor level. Applicants should demonstrate prowess in interdisciplinary, collaborative scientific research. The department will consider those developing methodologies with application to biomedical research in various areas, with particular interest in early detection and cancer screening, clinical trial design, imaging, and computer-intensive methodology—including machine learning, and integrative analyses of multiplatform high-dimensional data, such as genomic, proteomic, and microbiome analysis. A Ph.D. in statistics, biostatistics, or a related field is required.
The department has 19 faculty members, 37 masters and doctoral-level research analysts, and 10 postdoctoral fellows. Faculty members are actively involved in collaborative and methodological research in diverse areas such as clinical trial design, cancer screening and early detection, bioinformatics, genomic pathway analysis, network analysis, and integrative modeling of multiple types of complex data. This includes high-dimensional omic data, functional data analysis, Bayesian methodology, longitudinal and survival analysis, statistical genetics, population health research, and behavioral/social statistics.
Our faculty collaborate with world-class cancer scientists, such as Dr. James Allison—the 2018 Nobel Prize winner for medicine—in all cancer areas and research levels. Opportunities to support large-scale studies and programs include the Moon Shots Program, which brings together the top aspects of academia and industry to swiftly translate data into patient benefits. Their large, important cancer data sets require quantitative input with impact potential. Faculty also partner with our affiliated biostatistics doctoral programs at the University of Texas, Texas A&M University, and Rice University. Our department offers strong resources, including an in-house quantitative research computing team specializing in database design, web-based clinical trial support, scientific programming, and software engineering. For specifics, visit: https://biostatistics.mdanderson.org. Direct further questions to the selection committee chair.
The institution offers competitive salaries and an outstanding personal and professional benefits package. Houston is one of the world’s most innovative and diverse cities, with great neighborhoods; competitive private and public schools; a dynamic music, theater and sports scene; highly acclaimed museums; international cuisine; and year-round outdoor recreational activities.
MD Anderson is an equal opportunity employer and does not discriminate on the basis of race, color, national origin, gender, sexual orientation, age, religion, disability or veteran status, except where such distinction is required by law. All positions are security sensitive and subject to examination of criminal history record information. MD Anderson is a smoke-free and drug-free environment.
Consideration of applications will continue until the positions are filled. Applicants should send a cover letter outlining the relevance of their research experience and interests to the position, a curriculum vitae, a brief statement of current and proposed research, and three letters of recommendation to:
Faculty Search Committee
Department of Biostatistics
The University of Texas MD Anderson Cancer Center
P.O. Box 301402
Houston, TX 77230-1402Email: firstname.lastname@example.org
Successful candidates will join a team of biostatisticians working on a wide variety of collaborative projects in cancer research. The University of Texas MD Anderson Cancer Center supports and promotes professional growth and mentoring, as well as continuing education, creativity, and discovery.
Collaborate with clinicians and scientists to plan meaningful studies, statistically analyze and communicate/document the results:
- Assess relevant literature and existing data
- Perform simulations and complex statistical analyses using advanced statistical methods and programming
- Prepare statistical considerations for clinical trial designs or grant applications
- Perform biostatistical reviews of research protocols
- Collaborate on development of new statistical methodology
- Prepare written reports, including reports of data for committee and scientific meetings
- Collaborate with investigators on manuscripts
- Make original contributions to research projects
- Take initiative in professional activities
- If hired as or promoted to a senior position, participate in training and supervising junior statistical analysts
To be considered, send a letter of interest, curriculum vitae and three (3) letters of reference (include contact information for references) to email@example.com
- Master's degree in biostatistics, bioinformatics, statistics, computing, or related field
- Working knowledge of Windows and/or UNIX operating systems
- Experience in statistical programming and analysis
- Excellent oral and written communication skills in English
- Experience with mainframe and/or PC databases, document processing and statistical software such as SAS and S-Plus
- Experience writing reports and analytical sections of grant applications
- Extensive experience in statistical consulting, data analysis, design and management of clinical trials in the biomedical or cancer research setting
Salary: Competitive; commensurate with experience
EEO & Employment Eligibility
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, sexual orientation, gender identity/expression, disability, veteran status, genetic information or any other basis protected by MD Anderson policy or by federal, state or local laws, unless such distinction is required by law. All positions at MD Anderson Cancer Center are security sensitive and subject to examination of criminal history record information. MD Anderson Cancer Center provides a smoke-free and drug-free environment.
Postdoctoral Fellow Position
Postdoctoral fellow positions are currently available with the Department of Biostatistics. Please click here to learn of the specifics and to apply.