We are seeking a capable and experienced Senior Biostatistician to join the Bioinformatics team within the CMMR to work on large, diverse microbiome projects and multiomics datasets. The Senior Biostatistician will be required to provide statistical analysis for datasets produced by the standard CMMR bioinformatics pipelines, including 16S amplicon and Whole Genome Shotgun sequencing data, as well as metabolomics and proteomics data generated in other cores. Will work with the project team to determine project deliverables and provide a written report with figures and result interpretation. Will be responsible for deployment and development of analysis pipelines and utilizing data analysis pipelines written in-house in Perl, Python and/or Bash, using Linux computer clusters. The project deliverables are on a strict timeline, so having demonstrated problem-solving ability, strong communication skills (verbal and written) and the ability to work within a deadline is paramount.
Deploys, adapts, runs and validates multi-omics microbiome analysis pipelines, including 16S amplicon and Whole Genome Shotgun sequencing data, as well as metabolomics and proteomics data generated in other cores
Works with the project team to determine project deliverables and provide a written report with figures and result interpretation
Responsible for deployment and development of analysis pipelines and utilizing data analysis pipelines written in-house in Perl, Python and/or Bash, using Linux computer clusters
Performs statistical analysis and interpretation of multi-omics microbiome data for projects and research grants
Develops statistical programs for data manipulation and implementation of standard and advanced statistical methodology
Performs other tasks including protocol reviews, statistical report generation, manuscript preparation, review of statistical literature
Interacts and presents results to investigators in an effective manner
May assist and train users on computer programs
Master's Degree in Statistics, Biostatistics or a related field.
Three years of relevant experience.
Experience with advanced data science techniques such as deep learning and classification to identify potential disease drivers, biomarkers, and novel molecular profiles associated with disease
A degree in quantitative science (bio)statistics, bioinformatics, molecular biology, physics, etc
Experience in multi-omics analysis with applications to medical research and performing appropriate statistical analysis of the data. Additionally, experience with R, Python, Perl and Bash as well as programming using UNIX/LINUX clusters are desirable.
Experience with NGS data and metagenomic analyses are strongly desired.
Broad knowledge of biology, especially microbial ecology and/or genetics
Experience working with large omics data sets, data mining, and data analysis
Experience with UNIX and cluster computing desirable
R, Bash, Perl, Python or other scripting language experience
Experience with machine learning and/or artificial intelligence programming a plus
Demonstrated independent thinking and problem-solving ability
Strong oral and written communication skills
Ability to work in a team
Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.
Baylor College of Medicine fosters diversity among its students, trainees, faculty and staff as a prerequisite to accomplishing our institutional mission, and setting standards for excellence in training healthcare providers and biomedical scientists, promoting scientific innovation, and providing patient-centered care.
- Diversity, respect, and inclusiveness create an environment that is conducive to academic excellence, and strengthens our institution by increasing talent, encouraging creativity, and ensuring a broader perspective.
- Diversity helps position Baylor to reduce disparities in health and healthcare access and to better address the needs of the community we serve.
- Baylor is committed to recruiting and retaining outstanding students, trainees, faculty and staff from diverse backgrounds by providing a welcoming, supportive learning environment for all members of the Baylor community.