University of Missouri-Columbia
The Wan Influenza Systems Biology Lab seeks a highly motivated Statistician to join our dynamic research team. The successful candidate will support cutting-edge studies on immune responses from infection and vaccination exposure and viral transmission dynamics for influenza and emerging infectious diseases. Working closely with a multidisciplinary team of virologists, immunologists, computational biologists, and epidemiologists, the incumbent will design experiments, analyze complex datasets, develop predictive models, and contribute to high-impact publications and grant proposals.
This position offers a unique opportunity to work at the forefront of infectious disease biology, systems immunology, and predictive analytics, with research that has direct implications for epidemic prevention, control, and pandemic preparedness.
Key Responsibilities
Collaborate with principal investigators, postdoctoral fellows, and graduate students to design statistically rigorous animal, human, and surveillance studies. Perform power calculations, randomization strategies, and endpoint selection, providing statistical guidance for both laboratory and field studies. Support adaptive and complex study designs, particularly for multi-omics and high-throughput experiments. Develop predictive models for influenza and SARS-CoV-2 transmission, vaccine effectiveness, and antigenic variant emergence. Partner with computational scientists to create novel machine-learning models and interpret outputs to improve predictive performance. Conduct advanced statistical analyses (e.g., regression, mixed-effects models, Bayesian inference, time-series modeling) across diverse datasets, including serological assays (HAI, MN, ELISA, ELLA), aerosol size distribution, bioaerosol collection efficiency, single-cell RNA-seq, TCR/BCR repertoires, glycan microarrays, and multi-species surveillance data. Collaborate with computational scientists on next-generation sequencing (NGS), glycomics, and multi-omics analyses. Develop and integrate platforms for high-throughput experimental outcomes, including Tecan, bio-layer interferometry (BLI), qRT-PCR, and ELISpot assays. Create intuitive dashboards to monitor experimental results and surveillance metrics. Generate high-quality figures, tables, and statistical summaries for publications, grant proposals, and internal reports. Present analytical results at group meetings, collaborative workshops, and cross-institutional discussions. Develop and maintain statistical standard operating procedures (SOPs) to ensure consistency, reproducibility, and quality control. Perform sensitivity analyses, cross-validation, and model robustness assessments to strengthen study conclusions. Curate, document, and manage datasets in collaboration with team members to ensure data integrity and accessibility. Provide training workshops for graduate students, postdoctoral researchers, and technicians on statistical methods, data visualization, and software applications. Mentor junior researchers in developing reproducible computational workflows using SAS, R, Python, and related tools. Minimum Qualifications
A Bachelor's degree in related/relevant area and at least 2 years of experience from which comparable knowledge and skills can be acquired is necessary. Benefit Eligibility
This position is eligible for University benefits. As part of your total compensation, the University offers a comprehensive benefits package, including medical, dental and vision plans, retirement, paid time off, short- and long-term disability, paid parental leave, paid caregiver leave, and educational fee discounts for all four UM System campuses. Equal Employment Opportunity
The University of Missouri is an Equal Opportunity Employer.
#J-18808-Ljbffr
Collaborate with principal investigators, postdoctoral fellows, and graduate students to design statistically rigorous animal, human, and surveillance studies. Perform power calculations, randomization strategies, and endpoint selection, providing statistical guidance for both laboratory and field studies. Support adaptive and complex study designs, particularly for multi-omics and high-throughput experiments. Develop predictive models for influenza and SARS-CoV-2 transmission, vaccine effectiveness, and antigenic variant emergence. Partner with computational scientists to create novel machine-learning models and interpret outputs to improve predictive performance. Conduct advanced statistical analyses (e.g., regression, mixed-effects models, Bayesian inference, time-series modeling) across diverse datasets, including serological assays (HAI, MN, ELISA, ELLA), aerosol size distribution, bioaerosol collection efficiency, single-cell RNA-seq, TCR/BCR repertoires, glycan microarrays, and multi-species surveillance data. Collaborate with computational scientists on next-generation sequencing (NGS), glycomics, and multi-omics analyses. Develop and integrate platforms for high-throughput experimental outcomes, including Tecan, bio-layer interferometry (BLI), qRT-PCR, and ELISpot assays. Create intuitive dashboards to monitor experimental results and surveillance metrics. Generate high-quality figures, tables, and statistical summaries for publications, grant proposals, and internal reports. Present analytical results at group meetings, collaborative workshops, and cross-institutional discussions. Develop and maintain statistical standard operating procedures (SOPs) to ensure consistency, reproducibility, and quality control. Perform sensitivity analyses, cross-validation, and model robustness assessments to strengthen study conclusions. Curate, document, and manage datasets in collaboration with team members to ensure data integrity and accessibility. Provide training workshops for graduate students, postdoctoral researchers, and technicians on statistical methods, data visualization, and software applications. Mentor junior researchers in developing reproducible computational workflows using SAS, R, Python, and related tools. Minimum Qualifications
A Bachelor's degree in related/relevant area and at least 2 years of experience from which comparable knowledge and skills can be acquired is necessary. Benefit Eligibility
This position is eligible for University benefits. As part of your total compensation, the University offers a comprehensive benefits package, including medical, dental and vision plans, retirement, paid time off, short- and long-term disability, paid parental leave, paid caregiver leave, and educational fee discounts for all four UM System campuses. Equal Employment Opportunity
The University of Missouri is an Equal Opportunity Employer.
#J-18808-Ljbffr