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News
Baladandayuthapani to receive H.O. Hartley Award
Associate Professor Veera Baladandayuthapani has been selected as the 2018 recipient of the H.O. Hartley Award. This award is given annually by the Department of Statistics at Texas A&M University to an alumnus who demonstrates distinguished service to the statistics profession. Baladandayuthapani will receive the award July 30, 2018 at the TAMU reunion at the Joint Statistical Meetings.
MD Anderson Biostatistics at the Joint Statistical Meetings / JSM 2018
Faculty, analysts, postdoctoral fellows, and graduate researchers from the Biostatistics department are organizing sessions, giving presentations, and/or have coauthored work that will be presented at JSM 2018 in Vancouver, BC, Canada, July 28–August 2, 2018.
JSM Invited papers
Jeffrey Morris (presenter); Veera Baladandayuthapani & Postdoc Fellows Hojin Yang & Michelle Miranda, et al: Bayesian regression models for big spatially or longitudinally correlated functional data. Peng Wei (presenter); GRA Yiding Ma: A versatile and adaptive multiple functional annotations-based association test of whole-genome sequencing data. Ying Yuan (presenter), et al: Bayesian phase I/II biomarker-based dose finding for precision medicine with molecularly targeted agents. Suyu Liu (presenter), Ying Yuan, et al: A Bayesian phase I/II trial design for immunotherapy. Veera Baladandayuthapani (presenter), Jeffrey Morris & Min Jin Ha, et al: Pathway and network-based integrative Bayesian modeling of multiplatform genomic data. Hongtu Zhu (presenter): Deep learning in quantitative imaging analysis. Hongtu Zhu is the organizer of the topic: Deep Learning and Statistical Modeling with Applications. Peter Thall & Ying Yuan, et al: former postdoc Thomas Murray (presenter): Robust treatment comparison based on utilities of semi-competing risks in non-small-cell lung cancer.
JSM Contributed papers
Xuelin Huang is the organizer and Postdoctoral Fellow Yayuan Zhu is the chair for the topic: Survival Analysis Developments for Improving Medical Decision Making — Contributed Papers Xuelin Huang (presenter), et al: Optimal timing of stem cell transplant for leukemia patients. Senior Stat Analyst Nga Nguyen (presenter); Yisheng Li: Evaluating the performance of different confidence intervals for the Bland-Altman limits of agreement for non-normal data. Jian Wang (presenter); Sanjay Shete: Assessing indirect effect in a mediation model with a censored mediator. GRA Youyi Zhang (presenter); Jeffrey Morris & Veera Baladandayuthapani, et al: Bayesian integrative analysis of radiogenomics. Shouhao Zhou (presenter): Robust dose response estimation. Ying Yuan (presenter), et al: DCPAS: a Bayesian drug-combination platform design with adaptive shrinkage. Jing Ning & Xuelin Huang, et al: Efficient two-stage designs and proper inference for animal studies. Jeffrey Morris,, et al: Improved selection of high-dimensional neuroimaging biomarkers associated with neurodegenerative disease progression. Sanjay Shete, et al: Assessing current temporal and space-time anomalies of disease incidence. Donald Berry, et al: GBM AGILE: a phase II/III platform design with signature identification. Veera Baladandayuthapani & Jeffrey Morris, et al: Bayesian nonparametric differential analysis with application to colorectal cancer DNA methylation. Liang Li, et al: Dynamic prediction of competing risk events using landmark sub-distribution hazard model with multivariate longitudinal biomarkers. Veera Baladandayuthapani, et al: Bayesian group selection for compositional data: application to imaging genomic data for glioblastoma disease. Veera Baladandayuthapani, et al: Bayesian variable selection in multivariate nonlinear regression with graph structures.
JSM Posters
Senior Stat Analyst Wei Qiao (presenter); Xuelin Huang & Jing Ning: Clinical trial design comparison with covariate-adjusted and response adaptive randomization. Research Stat Analyst M. Laura Rubin (presenter), et al: Effect of longitudinal intracranial pressure on ordinal Glasgow outcome scale using a joint model approach. Jeffrey Morris, Rice University GRA (presenter): Bayesian functional quantile regression. Liang Li, et al: Using stratified propensity score matching approach to adjust risk assessment for breast reconstruction patients . Nabihah Tayob, et al: Nonparametric group sequential methods for recurrent and terminal events from multiple follow-up windows.
Lee a Keynote Speaker at BAYES 2018 Cambridge: Bayesian Biostatistics Workshop
Professor J. Jack Lee, Kenedy Foundation Chair in Cancer Research, was a keynote speaker at the Bayesian Biostatistics Workshop, held June 20-22 in Cambridge, UK. The workshop was a satellite event of the 2018 International Society for Bayesian Analysis (ISBA) World Meeting.
Ning awarded Sabin Fellowship
Associate Professor Jing Ning has been named a recipient of MD Anderson's Andrew Sabin Fellowship for the category of population and quantitative sciences.
Publication named Editor's Choice in Medical Physics
Principal Statistical Analyst Auston Wei collaborated with investigators in the Imaging Physics department on research for which the corresponding publication has been selected as the editor's choice for the month of April 2018 by the journal Medical Physics. The article is titled Development of a dual-energy computed tomography quality control program: Characterization of scanner response and definition of relevant parameters for a fast-kVp switching dual-energy computed tomography system.
Baladandayuthapani featured in MD Anderson's Annual Report: Meet the architects who design treatment-enhancing clinical trials
Associate Professor Veerabhadran Baladandayuthapani is featured as a vital member of clinical research teams at MD Anderson.
Morris featured in MD Anderson's Cancer Frontline: Using integromics to better understand and treat colorectal cancer
Professor Jeffrey S. Morris describes some of the collaborative work he is undertaking with members of the Colorectal Cancer Subtyping Consortium and MD Anderson's Colorectal Cancer Moon Shot.
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.
12 biostatistics faculty are ASA fellows
Twelve 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), Ziding Feng (1997), Kim-Anh Do (2006), Yu Shen (2007), J. Jack Lee (2008), Jeffrey S. Morris (2011), Sanjay Shete (2012), Peter F. Thall (2015), Veerabhadran Baladandayuthapani (2016), Kenneth R. Hess (2017), Xuelin Huang (2017), and Ying Yuan (2017).
Faculty Position
Assistant or Associate Professor
The Department of Biostatistics at MD Anderson Cancer Center is seeking candidates for one tenured/tenure-track faculty position at the level of Assistant or Associate Professor. The department invites applications from qualified individuals able to establish themselves as research leaders and demonstrate prowess in interdisciplinary collaborative scientific research. We will consider researchers who can contribute to the development of methodology and its applications to biomedical research in various areas, but are especially interested in research areas relating to integrative analyses of multi-platform genomic data, high-dimensional biomedical data and microbiomic data. A Ph.D. in statistics, biostatistics or a related field is required.
Faculty members are actively involved in collaborative and methodological research in such diverse areas as clinical trial design; Bayesian methodology; cancer screening and early detection; bioinformatics; genomic pathway analysis; integrative modeling of multiple types of complex data, including high-dimensional genomic data; functional data analysis; image data analysis; survival analysis; statistical genetics; and behavioral/social statistics. Faculty members also have opportunities in the affiliated biostatistics doctoral programs at the University of Texas Health Science Center, Rice University, and Texas A&M University. The department is supported by strong resources, which include an active quantitative research computing team with specialties in database design, web-based clinical trial support, scientific programming, and software engineering.
MD Anderson Cancer Center offers competitive salaries and an outstanding personal and professional benefits package. Houston is one of the world’s most innovative and diverse cities, nurturing great neighborhoods, competitive private and public schools, an exceptional music and theater scene, highly acclaimed museums, international cuisine, and year-round outdoor recreational activities.
The University of Texas MD Anderson Cancer Center 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 at The University of Texas MD Anderson Cancer Center are security sensitive and subject to examination of criminal history record information. MD Anderson Cancer Center is a smoke-free and drug-free environment.
Consideration of applications will continue until the position is filled. Interested applicants should email (or mail): a cover letter outlining the relevance of their research experience and interests to the position description, a curriculum vitae, a brief statement of current and proposed research plans, 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 77230-1402
Email: biostat-search@mdanderson.org
Statistical Analyst Position
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.
Responsibilities
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 dqs-stat-job@mdanderson.org
Minimum Qualifications:
- 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
Desired Qualifications:
- 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
Position with Liang Li, Ph.D.
This position will start June 2018 or thereafter.
Area: biostatistical methodologic research and application
Objective: conduct research and publish the results. Under the supervision of Dr. Liang Li, the postdoctoral fellow will work on challenging and important clinical and biological projects that involve complex statistical modeling and computation.
Primary focus: joint modeling of longitudinal and survival data, dynamic prediction, and statistical learning methods for large data sets
Qualifications / Research interest: strong theoretical training in statistics/biostatistics; expertise in survival and longitudinal data analysis; strong programming and computational skills; interest in statistical methodology research; extensive experience in R; some experience with machine learning is desirable
This position will remain open until it is filled.
Application: Send résumé and a cover letter summarizing your research background and interest to:
Liang Li
Department of Biostatistics
The University of Texas MD Anderson Cancer Center
Houston, TX 77030
LLi15@mdanderson.org
Salary: $65,000 USD/year
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 discrimination 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.
Position with Jeffrey S. Morris, Ph.D.
Area: Computational statistics with applications in biostatistics and bioinformatics
Duties & Responsibilities: The research will involve developing novel statistical and computational methodology for the analysis of functional and imaging data, with a special focus on complex, high-dimensional functions and images. One project of interest is Bayesian methods for LC/MS proteomic data, combining biological knowledge and functional data modeling techniques using fast approximate Bayesian computational procedures. Other application-driven methodological research may also be undertaken, with other application areas including event-related potentials (ERP), diffusion MRI methods such as DTI/MAP-MRI, functional data on the sphere and multivariate real-time time series from glaucoma studies, and various types of genomic data that can be modeled in an integrated fashion with corresponding clinical outcome data collected from large numbers of patients with colon cancer. The genomic data may include copy number alterations, methylation, miRNA, ncRNA, microarray, RNAseq, and proteomic data. We have a working group carrying out deep characterization of newly established molecular subtypes of colon cancer (Guinney et al. 2015, Nature Medicine), which involves many potential projects in data integration that we hope will lead to new strategies in precision therapy.
Qualifications: We seek a highly motivated individual with a Ph.D. in statistics/biostatistics or related quantitative fields. Must have strong methodologic training in statistics/biostatistics; strong programming skills, in particular R/Matlab, and possibly one lower-level computer language such as C or Fortran; and interest in statistical methodology research. Interest or background in neuroimaging, bioinformatics, genomics, or proteomics is a plus. Expertise or skills in any of the following areas is desirable: analysis of high-dimensional data, Bayesian MCMC computations, approximate Bayesian computational methods, variable selection and sparsity priors, linear models, nonparametric regression, spatio-temporal data, multivariate techniques, functional data analysis, and image data analysis.
Application: Send a cover letter, CV, and research statement (with three references and their contact information) to:
pcunning@mdanderson.org
and
jefmorris@mdanderson.org
Subject line: Morris postdoc
Application deadline: Consideration of applications will begin immediately, and continue until the positions are filled.
Salary: $65,000 USD/year
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 discrimination 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.