Students
Graduate students in the Division of Biology & Biomedical Sciences at Washington University School of Medicine are welcome to contact Dr. Turner to discuss potential rotation projects. WashU undergraduates interested in research experience may also reach out to Dr. Turner to explore available opportunities.
Postdoctoral fellows
The Turner Lab currently has a posting for a postdoctoral position. Details of this position include:
The Turner Lab at Washington University in St. Louis focuses on advancing the emerging field of Precision Genomics, which we define as “determining all possible relevant genomic variation within an individual to the precise nucleotide.” Precision Genomics is a cornerstone under the umbrella of Precision Medicine, addressing critical challenges in genomic interpretation and translation. The lab investigates fundamental limitations to achieving comprehensive genomic insights, including:
- Interpretation of noncoding variation
- Variants missed due to current genomic technologies
- Speed and efficiency of genomic workflows
- Combined effects of rare and/or common multi-hit variants
- Gene × environment interactions
The lab employs a range of approaches, including cutting-edge sequencing technologies, computational genomics, functional assays, and integrated data analysis. We are seeking a highly motivated postdoctoral researcher who shares our passion for solving foundational problems in human genetics and genomics, with expanded interests in computational biology, functional genomics, and neuroscience.
Primary Duties and Responsibilities:
- Conduct independent and collaborative research, under the supervision of Dr. Turner, focused on one or more of the five major challenges outlined in Precision Genomics
- Develop and apply computational and/or experimental techniques to identify and interpret genomic variation
- Analyze large-scale genomic and multi-omic datasets using custom and existing pipelines
- Design and implement functional validation assays for candidate variants, genes, or regulatory elements
- Present research findings at national and international conferences, and contribute to high-impact publications
- Mentor graduate students and contribute to lab meetings and collaborative projects within the university and with external partners
Example Projects
- Noncoding Variation in Neurodevelopmental Disorders: Investigating the functional impact of noncoding genetic variants in neurodevelopmental disorders, including the identification of novel regulatory elements and their roles in brain development.
- Genotype-Phenotype Correlations in 9p-Related Syndromes: Investigating the genotype-phenotype correlations in 9p-related syndromes (e.g., 9p deletion syndrome, 9p duplication syndrome), identifying specific genomic variants and their relationship to clinical manifestations, and understanding the molecular mechanisms behind these rare disorders.
- Methods Development: Developing novel computational tools, pipelines, or algorithms to improve the accuracy and speed of genomic workflows, particularly for rare variants and noncoding regions.
- Functional Follow-up: Implementing functional assays to validate the effects of candidate variants, such as CRISPR-based gene editing or RNA-seq to assess gene expression changes, and linking these findings to clinical phenotypes.
- Examining Differences in Autism and Cancer: Exploring how genomic variation in common pathways contributes to both neurodevelopmental disorders like autism and cancers, focusing on shared regulatory mechanisms, genetic overlap, or specific mutations that may affect both conditions.
Qualifications
Recent PhD, MD/PhD or equivalent in Genetics, Genomics, Bioinformatics, Molecular Biology, Computational Biology, Neuroscience, Oncology, or a related field
- At least two first-author publications in peer-reviewed journals
- Strong publication record demonstrating independent research ability
- Proficiency in one or more of the following: next-generation sequencing analysis, statistical genetics, genome editing, or functional genomics
- Experience with high-performance computing and parallel computing techniques including working in the cloud
- Experience with regulatory genomics, noncoding variant interpretation, or genome assembly/structural variant detection
- Experience with high-throughput molecular biology assays
- Experience with complex functional experiments
- Background in machine learning, AI, or data integration for genomic datasets
- Familiarity with gene-environment interaction studies
- Strong programming skills (e.g., C++, Rust, Python, R, or equivalent)
- Excellent communication skills and ability to work both independently and in a collaborative, multidisciplinary environment
