Overview
On Site
USD 93,156.00 - 186,311.00 per year
Full Time
Skills
Biology
RNA
Collaboration
Analytics
Data Acquisition
Modeling
Evaluation
Reporting
Machine Learning (ML)
Python
R
Assembly
Mapping
Dashboard
Design Of Experiments
Resource Allocation
Training
Research
Open Source
Workday
Nursing
Science
Military
Job Details
The Sheynkman Laboratory seeks a senior-level data scientist to drive integrative analytics at the interface of alternative splicing biology, long-read RNA sequencing, splicing-QTL discovery and proteoform characterization. You will collaborate closely with faculty, post-docs and students to convert complex multi-omics data into actionable insights and predictive models that illuminate isoform-specific disease mechanisms.
Core duties
Act as analytics thought-leader from scope definition through deployment: data acquisition, preparation, modelling, evaluation and reporting.
Build and maintain statistical / machine-learning pipelines (Python / R; Snakemake/Nextflow) for long-read transcriptome assembly, sQTL fine-mapping (SuSiE, Leafcutter) and proteogenomic isoform detection.
Integrate disparate datasets (PacBio/ONT, Illumina, Orbitrap MS, CRISPR screens) to uncover novel correlations and develop predictive models of isoform function.
Visualize findings in dashboards and bespoke figures for faculty and external stakeholders; deliver routine and ad-hoc reports that guide experimental design and resource allocation.
Provide methodological guidance and informal training to junior analysts and wet-lab scientists; champion reproducible research and FAIR data principles.
Contribute to grant proposals, manuscripts, and open-source software released by the lab.
MINIMUM REQUIREMENTS
Education: Master's degree required. PhD preferred.
Experience: 5-10 years relevant experience.
Licensure: None required
TO APPLY
PROCESS FOR INTERNAL UVA APPLICANTS: Please apply through your Workday Home page, search "Find Jobs", and search for "R0072449"
PROCESS FOR EXTERNAL APPLICANTS: Please APPLY HERE
Complete an application online and attach:
CV/Resume
Cover Letter detailing your interest in this position
Salary range: 93,156.00 - 186,311.00 USD Annual
Please note that you MUST upload ALL required documents. Applications that do not contain ALL of the required documents will not receive full consideration.
For questions about the application process, please contact Eric Allen, Academic Recruiter, at . For Questions regarding the position, please contact Dr. Gloria Sheynkman at
PHYSICAL DEMANDS
This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.
The University of Virginia, i ncluding the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physicians Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff. We believe diversity is excellence expressing itself through every person's perspectives and lived experience. We are equal opportunity employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex, pregnancy, sexual orientation, veteran or military status, and family medical or genetic information.
Core duties
Act as analytics thought-leader from scope definition through deployment: data acquisition, preparation, modelling, evaluation and reporting.
Build and maintain statistical / machine-learning pipelines (Python / R; Snakemake/Nextflow) for long-read transcriptome assembly, sQTL fine-mapping (SuSiE, Leafcutter) and proteogenomic isoform detection.
Integrate disparate datasets (PacBio/ONT, Illumina, Orbitrap MS, CRISPR screens) to uncover novel correlations and develop predictive models of isoform function.
Visualize findings in dashboards and bespoke figures for faculty and external stakeholders; deliver routine and ad-hoc reports that guide experimental design and resource allocation.
Provide methodological guidance and informal training to junior analysts and wet-lab scientists; champion reproducible research and FAIR data principles.
Contribute to grant proposals, manuscripts, and open-source software released by the lab.
MINIMUM REQUIREMENTS
Education: Master's degree required. PhD preferred.
Experience: 5-10 years relevant experience.
Licensure: None required
TO APPLY
PROCESS FOR INTERNAL UVA APPLICANTS: Please apply through your Workday Home page, search "Find Jobs", and search for "R0072449"
PROCESS FOR EXTERNAL APPLICANTS: Please APPLY HERE
Complete an application online and attach:
CV/Resume
Cover Letter detailing your interest in this position
Salary range: 93,156.00 - 186,311.00 USD Annual
Please note that you MUST upload ALL required documents. Applications that do not contain ALL of the required documents will not receive full consideration.
For questions about the application process, please contact Eric Allen, Academic Recruiter, at . For Questions regarding the position, please contact Dr. Gloria Sheynkman at
PHYSICAL DEMANDS
This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.
The University of Virginia, i ncluding the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physicians Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff. We believe diversity is excellence expressing itself through every person's perspectives and lived experience. We are equal opportunity employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex, pregnancy, sexual orientation, veteran or military status, and family medical or genetic information.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.