Bioinformatics Research Assistant (Contingent II - Grant Funded))

Maryland Connect•Patuxent Riding, MD

About The Position

The Department of Natural Sciences and Mathematics at Bowie State University seeks a highly motivated Bioinformatics Research Assistant to support biomedical research into molecular mechanisms underlying disease phenotypes in cancer and associations between disease phenotypes and mitochondrial genetic variation. This grant-funded position contributes to genomics research through computational analysis of large-scale biological datasets in a collaborative, interdisciplinary research environment. The Bioinformatics Research Assistant works closely with the Principal Investigator, undergraduate researchers, and collaborators to support bioinformatics analyses, manage computational workflows, and contribute to research dissemination. A core part of the position is training, mentoring, and supporting undergraduate researchers, particularly students from groups historically underrepresented in STEM. Continued employment depends on the availability of grant funding and continuation of the project's approved scope. Occasional evening or weekend activities may be required for student research, project deadlines, conferences, or grant-related events.

Requirements

Bachelor's degree in Bioinformatics, Computational Biology, Biology, Data Science, or a related field and at least two years of relevant experience, or a master's degree in Bioinformatics, Computational Biology, Computer Science, Genomics, Data Science, Biology, or a closely related field.
Demonstrated experience performing computational analyses of biological or genomic data.
Proficiency with Unix/Linux operating systems and command-line environments.
Experience with scripting or programming languages commonly used in bioinformatics, such as Python, R, Perl, or related languages.
Experience managing and analyzing large datasets.
Strong analytical, organizational, and problem-solving skills.
Effective written and oral communication skills.
Ability to work independently and contribute effectively within a collaborative research team.

Nice To Haves

Experience using high-performance computing (HPC) environments.
Familiarity with workflow management systems and reproducible research practices.
Experience with statistical genetics, genomics, mitochondrial genetics, cancer genomics, or related research areas.
Experience mentoring, teaching, or training undergraduate students.
Demonstrated commitment to supporting students from underrepresented and diverse backgrounds in STEM.
Evidence of research productivity, including scientific presentations, publications, or other scholarly contributions.

Responsibilities

Perform bioinformatics and computational analyses of genomic and other large-scale biological datasets related to cancer and mitochondrial genetics research.
Develop, maintain, and optimize data analysis workflows and bioinformatics pipelines.
Assist with data management, quality control, statistical analysis, visualization, and interpretation of research findings.
Support preparation of research reports, scientific presentations, manuscripts, and grant-related documentation.
Participate in collaborative research with faculty, students, and external research partners.
Manage software installations and computational resources in Unix/Linux environments and troubleshoot technical issues.
Maintain accurate research records, documentation, and data management procedures.
Assist with laboratory and project operations as needed to support grant objectives.
Train undergraduate students in bioinformatics, computational biology, and research best practices.
Provide students technical guidance on data analysis methods, software tools, and computational workflows.
Support student participation in research projects, presentations, and scholarly activities.
Foster an inclusive, supportive, and collaborative learning environment for students from diverse backgrounds.
Contribute to a research culture that promotes student success, scientific curiosity, and persistence in STEM fields.