Research Associate 2

ORAU•Oak Ridge, TN

3d•$35 - $49•Remote

About The Position

The early career research associate will propose and conduct research under the guidance of a self-selected mentor, that leverages National Institute of Health (NIH) Common Fund datasets and resources to address complex biological questions. The research conducted will center on integrative analysis across multiple NIH Common Fund datasets with a focus on developing computational strategies that enable discovery across independently generated data resources. The early career research associate will contribute to the Common Fund Data Ecosystem (CFDE) community through dissemination of findings, development of reproducible workflows, and active engagement in collaborative initiatives offered through the CFDE community, supporting broader efforts to advance biomedical data integration and reuse. Often early career research associates encounter complex scientific and technical problems that require independent analysis, critical thinking, and consultation with a research mentor and collaborators. Problems are often novel and do not have established solutions. Example: Integrating heterogeneous datasets from multiple NIH Common Fund programs that differ in data formats, standards, metadata, and quality. These challenges are resolved by developing computational workflows, applying data harmonization techniques, and using appropriate statistical and bioinformatics methods.

Requirements

Master’s degree and 1-2 years of directly related experience.
Ph.D. preferred in Bioinformatics, Biomedical Informatics, Computational Biology, Molecular Biology, Data Science or a closely related field and 0 years of experience.
An equivalent combination of education and experience performing duties as described may be substituted for the minimum requirements.
Note: It is REQUIRED that any Ph.D. earned must have been earned within the past 5 years.
Applicants must submit a research proposal (limited to one page) describing their planned research. Proposals must include: A description of how the research will use data from TWO or more CFDE datasets (https://cfdeknowledge.org/r/kc_landing), Any CFDE resources, tools, or support needed to successfully complete the research, A summary of the applicant’s prior experience with any omics related data, if any in addition to working with CFDE data (note: prior experience with CFDE data is not required for selection).
Demonstrated research experience in computational biology, data science, bioinformatics, biomedical informatics, molecular biology, or related field, including analysis of complex biomedical datasets, use or development of reproducible computational workflows, scientific publication and presentation, and collaboration with multidisciplinary research teams. Experience gained through doctoral research, postdoctoral training, or equivalent research experience is acceptable.
This position requires a blend of biological expertise, computational skills, and collaborative abilities to advance integrative biomedical research using NIH Common Fund data and resources.
Knowledge of computational biology, bioinformatics, data science, molecular biology or a related field, with an understanding of biomedical research and multi-omics data analysis.
Demonstrated ability to apply computational, statistical, and analytical methods to integrate and analyze complex biomedical datasets.
Proficiency in programming and data analysis tools commonly used in biomedical research (e.g., R, Python, or similar).
Strong scientific communication skills, including the ability to prepare publications, presentations, and reproducible research outputs.
Ability to work independently under the guidance of a mentor while effectively collaborating with interdisciplinary teams and the broader CFDE community.
Strong organizational, critical thinking, and problem-solving skills, with the ability to manage multiple priorities and contribute to collaborative research initiatives.

Nice To Haves

Ph.D. preferred in Bioinformatics, Biomedical Informatics, Computational Biology, Molecular Biology, Data Science or a closely related field and 0 years of experience.
prior experience with CFDE data is not required for selection

Responsibilities

Conduct research with a focus on applying computational, bioinformatics, and statistical approaches to address complex biological questions using diverse datatypes including omics (e.g., spatial, multi-omics, single-cell, genomics, transcriptomics, proteomics, metabolomics) and biological entities (e.g., cell, connectivity, tissue, drug, organ).
Regular engagement and meetings with selected mentor to ensure guidance on leveraging CFDE data and resources to address complex biological questions, discuss research progress, and alignment with achieving proposed research.
Developing publications, conference presentations, reproducible workflows, and other project outputs to the CFDE community and wider research community.
Participation in CFDE annual meetings, events, presentations, mentoring opportunities, or other community-facing activities.
Other tasks as assigned.