Senior Bioinformatician Data Analyst, Department of Genome Sciences

State of Virginia•Charlottesville, VA

47d•Onsite

About The Position

The Department of Genome Sciences at the University of Virginia is seeking a candidate for the role of Senior Biostatistician Data Analyst in the Miller Lab . This is an outstanding opportunity to gain practical experience implementing advanced bioinformatics and computational genomics tools in a unique collaborative setting and to establish a deeper understanding of precision medicine. In addition, you will contribute to published manuscripts and engage in international conferences with multidisciplinary academic and industry experts. Founded in 1819 by Thomas Jefferson, the University of Virginia (UVA) is renowned for its commitment to advancing human knowledge, educating leaders, and cultivating an informed citizenry. The Department of Genome Sciences (formerly Center for Public Health Genomics) addresses fundamental questions in biology, public health, and medicine by developing and applying state-of-the-art genetic, genomic, and computational approaches to complex human diseases. The Miller Lab focuses on unravelling cardiovascular diseases by integrating large-scale human genetics, single-cell/spatial multi-omics, and data science approaches. UVA is a member of an international consortium, NextGen , recently funded by the European Union and includes 22 partners from academia and industry. In NextGen, we are building novel and synergistic tools to enable portable multimodal, multiomic and clinically oriented research in high-impact areas of cardiovascular medicine. NextGen tools will benefit researchers, innovators and healthcare professionals by identifying and overcoming health data linkage barriers in exemplar use cases which are complex or intractable with existing technology. Consequently, it will benefit patients, providing faster diagnosis, and more targeted treatments.

Requirements

Master's degree
Five years of related experience.

Nice To Haves

MS or PhD in a quantitative discipline (e.g., Bioinformatics, Statistics, Computational Biology, Engineering).
Experience in analyzing genomics or multi-omics datasets.
Proficiency in data analysis and computational modeling using R, Python, Bash, etc.
Experience with automated pipelines and workflows (HPC, GitHub, Docker).
Strong understanding of biology, physiology, human genetics, and machine learning.
Excellent communication skills for both technical and broad audiences.
Demonstrated ability to innovate and solve complex problems.
Strong networking and teamwork skills.

Responsibilities

Apply single-cell and spatial genomic data analyses to develop and benchmark pipelines for a pan-vascular tissue atlas of atherosclerosis.
Utilize expertise in bioinformatics, statistics, data science, and machine learning to infer novel cell states, gene regulatory networks, and druggable protein targets.
Enhance understanding of disease-associated genes, signaling pathways, and regulatory mechanisms for coronary artery disease (CAD).
Develop precise targeting strategies and risk profiles for causal disease pathways underlying CAD and related cardiometabolic diseases.
Work with your PI, lab members and other collaborators to curate human single cell and multi-omics datasets and apply automated pipelines to refine cell states and disease trajectories
Work with your PI, lab members and collaborators to refine AI/ML models to predict gene perturbations, regulatory networks and treatment responses
Develop new user-friendly web interfaces to explore datasets and AI/ML predictions
Communicate results through peer-reviewed publications, internal and external presentations, conferences, and websites