Bioinformatics Postdoctoral Research Associate, Genome Sciences

The Rector & Visitors of the University of Virginia; Charlottesville, Virginia, Evanston Township (VA, MN, IL); On-site; USD 60,000 - 100,000; Full time

Job summary

An established academic institution is seeking a highly motivated Postdoctoral Research Associate to join a dynamic lab focused on cutting-edge genomic research. This role involves applying advanced machine learning techniques to analyze complex genomic datasets, aiming to uncover novel insights into cardiovascular diseases. The successful candidate will collaborate with a team of experts, develop innovative AI models, and contribute to impactful research publications. This is an excellent opportunity for those looking to advance their academic careers in a supportive and intellectually stimulating environment, with the potential for long-term growth and development.

Qualifications

• Experience with large-scale datasets from public repositories for data analysis.
• Strong skills in machine learning algorithms for genomic data analysis.
• Excellent communication skills for manuscript writing and presentations.

Responsibilities

• Develop and refine AI/ML models to discover cardiovascular disease networks.
• Curate human single-cell genomic datasets and apply federated learning models.
• Communicate results through publications and presentations.

Skills

Machine Learning

Data Science

Genomics

Bioinformatics

Statistical Modeling

Problem-Solving

Communication Skills

Education

Doctoral degree in a quantitative discipline

Tools

R

Python

Bash

Git/GitHub

Nextflow

Snakemake

Docker

Job description

The Department of Genome Sciences at the University of Virginia is seeking a highly motivated candidate for a Postdoctoral Research Associate position in the Miller Lab. The successful candidate will apply state-of-the-art machine learning algorithms and custom disease-relevant genomic datasets (e.g., coronary artery single-nucleus chromatin accessibility and RNA sequencing) to develop targeted cardiovascular treatments.

In this role you will apply both machine learning predictive modelling and human genetic analyses of non-coding regulatory sequences to identify cell-specific targets for coronary artery disease (CAD). You will apply expertise in data science, machine learning, as well as multi-omics integration to predict and validate functional regulatory networks in vascular cell types. This work will enhance our understanding of disease-relevant cis-acting elements and trans-acting effector proteins and metabolites. With the knowledge generated from these analyses you will work to develop more precise targeting strategies against the primary disease-causing pathways for CAD and related cardiometabolic diseases.

The successful candidate will be expected to:

• Work with your PI and collaborators to develop and refine artificial intelligence/machine learning models to discover novel cardiovascular disease networks and biomarkers

• Work with your PI and other AI/ML scientists in NextGen to curate human single cell genomic datasets and apply federated learning models to predict CVD risk, disease drivers, 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.

Minimum Requirements:

• Doctoral degree in a quantitative discipline such as computer science, engineering, bioinformatics, computational biology, or related fields.

Preferred Qualifications:

• Multi-Omics and Genomics Expertise: Strong experience with large-scale datasets from public repositories, crucial for data analysis and research.

• Machine Learning Skills: Experience with machine learning algorithms, transformers, or large language models to analyze genomic data.

• Computational Proficiency: Skilled in R, Python, Bash, and other programming languages for data analysis and statistical modeling.

• Automated Workflows Experience: Proficient in using HPC, Git/GitHub, Nextflow, Snakemake, or Docker for efficient pipeline development.

• Biological Sciences Knowledge: Solid understanding of cellular/molecular biology, physiology, and genetics.

• Communication Skills: Excellent in manuscript writing and oral presentations, with the ability to convey complex information clearly.

• Problem-Solving and Innovation: Able to identify opportunities, learn quickly, and apply innovative solutions.

• Teamwork and Collaboration: Strong team collaboration skills, effective in multi-disciplinary environments.

This position will sponsor applicants for work visa who meet the qualifications.

This position is offered as a 12-month appointment, with the possibility of renewal up to three years based on performance and funding. This role is designed as a training opportunity in preparation for a full-time academic or research career.

This position will remain open until filled. The University will perform background checks on all new hires prior to employment.A completed pre-employment health screen is required for this position prior to employment.

This is an Exempt level, benefited position. For more information on the benefits at UVA, visit hr.virginia.edu/benefits

Anticipated Hiring Range:

Competitive Salary, commensurate with education and experience, in accordance with NIH guidelines.

Physical Demands:

This position is located in Charlottesville, VA

To Apply:
Please apply through Careers at UVA, and search for R0068607.
Internal applicants must apply through their UVA Workday profile by searching 'Find Jobs.'
Complete an application online with the following documents:

• CV

• Cover letter

• Contact information for 3 references

Upload all materials into the resume submission field, multiple documents can be submitted into this one field. Alternatively, merge all documents into one PDF for submission. Applications that do not contain all required documents will not receive full consideration.

For questions about the application process, please contact Yelena Markazyan, Academic Recruiter at [e-mail]

For more information about UVA and the Charlottesville community please see http://www.virginia.edu/life/charlottesvilleand https://embarkcva.com/

The University of Virginia, including the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician's 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 experiences. 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.