Research Scientist in Biomedical Data Science

Dartmouth College; Lebanon (NH); Vor Ort; USD 90.000 - 120.000; Vollzeit

Zusammenfassung

Dartmouth College's Genomic Data Science Core (GDSC) seeks a Research Scientist to analyze next-generation sequencing data and provide biological insights. The core provides computational support to Dartmouth faculty and manages multiple genomic modalities.

The ideal candidate will have experience with RNA-seq, ATAC-seq, WES, WGS, ChIP-seq, and metagenomics, plus scripting in Bash, R, or Python, and familiarity with workflow tools like Snakemake or Nextflow.

Qualifikationen

• The candidate must hold a BS degree in genomics, bioinformatics, data science, or related field.
• Proficiency with BASH and R or Python is required.
• Minimum five years of relevant genomics data analysis experience.
• Experience analyzing next-generation sequencing data is essential.

Aufgaben

• Contribute to experimental design and develop data analysis plans.
• Perform genomic data analysis for core users.
• Maintain open communication with users and meet deadlines.
• Develop and maintain genomic data analysis pipelines and workflows.
• Present analyses at meetings and assist in publications and grants.

Kenntnisse

BASH

R

Python

Organizational skills

Independent work

Genomics experience

Ausbildung

BS degree in genomics or related field

Tools

Snakemake

Nextflow

Conda

Docker

Git/GitHub

IGV

GEO/SRA

Jobbeschreibung

Dartmouth College: Geisel School of Medicine: Department of Biomedical Data Science

Location

Lebanon, New Hampshire

Open Date

Oct 31, 2026

Description

The Genomic Data Science Core (GDSC), part of the Center for Quantitative Biology at Dartmouth, is seeking a Research Scientist to analyze next generation squencing data and provide biological insight to the results. The GDSC is a fee-for-service bioinformatics core facility aimed at providing computational expertise to the Dartmouth faculty in advancing their research goals. The Research Scientist will work as part of the GDSC team to analyze high-dimensional genomic datasets. The ability to work effectively as part of a team is essential to be successful in this position.

The ideal candidate is expected to have knowledge and/or experience analyzing large datasets from multiple major genomic modalities such as RNA-seq, ATAC-seq, WES, WGS, ChIP-seq, and metagenomics. Experience with other types of genomic data (e.g. methylation/SNP arrays, TCR-seq, Nanostring) is a plus, and experience with single-cell or spatial transcriptomics is especially desirable. The candidate should have familiarity with computational tools used for these analyses and the ability to write scripts in BASH, R, and/or Python. Furthermore, the candidate should have a working knowledge of basic statistical concepts (regression analysis, linear modeling, probability). Experience with any of the following are also highly desirable: use of workflow management software (e.g. Snakemake, Nextflow) to construct and maintain data analysis pipelines, software management with package managers (e.g. Conda) or containers (e.g. Singularity or Docker), version control with Git/GitHub, familiarity with public genomics databases (GEO, SRA, NCBI, Ensembl), experience with genome browsers (e.g. IGV), high performance computing systems and/or cloud computing environments (GCP, AWS).

Researchers at Dartmouth encompass a broad range of biological disciplines, including cancer biology, immunology, neurology, microbiology, and environmental science. As such, the candidate must have a desire to work in a highly collaborative research environment and possess strong communication and organizational skills to manage and multitask diverse analysis projects. The Research Scientist will be responsible for tracking his/her time committed to each project for billing purposes. Due to the service-based nature of this role, being able to work to established deadlines is a crucial requirement. Presenting at conferences and seminars is encouraged, and opportunities for career development such as workshops and coursework will be supported.

Primary Responsibilities

Note: This position is dependent on the availability of sponsored funding.

• Contribute to experimental design and development of appropriate data analysis plans.
• Perform genomic data analysis for core users.
• Establish and maintain an open line of communication with users working to deadlines and specifications outlined in the analysis plan.
• Provide clear and detailed analysis summary reports to core users.
• Develop and maintain genomic data analysis pipelines and workflows.
• Use RADAR for analysis time and fee tracking.
• Work in a collaboratively and participate in team meetings as well as meetings with core users.
• Provide scientific training and mentoring to other core members or core users where required.Assist in the preparation of publications and grant proposals.
• Become familiar with all services offered and serve as a point of contact for users.
• Present at local, regional, and national meetings to expand the visibility of the core.
• Engage in professional development opportunities such as workshops and courses to acquire new skills.
• Performs other duties as required.

Minimum Qualifications

• Proficiency with BASH and R or Python.
• Proven organizational skills with exceptional attention to detail.
• Ability to work independently, taking initiative to advance projects.
• Demonstrated experience analyzing next generation sequencing data.
• Ability to use sound judgment and communicate effectively with users and facility staff.
• Ability to effectively collaborate and interact with all levels of staff and management.
• At least five years of relevant experience.
• Requires a minimum of a BS degree with experience in genomics, bioinformatics, data science, or a related field.

Preferred Qualifications

• Experience working in a core facility or other customer-facing or service-oriented role.
• Experience analyzing single cell and/or spatial genomic data.
• Experience optimizing computational workflows to increase efficiency and improve turnaround times.
• Basic understanding of molecular biology, immunology, microbiology or cancer biology.