Research Scientist

University of Colorado•Aurora, CO

1d•Remote

About The Position

The candidate will support a basic-translational research program focused on lung biology by analyzing high-throughput sequencing data, including bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomics, to investigate gene expression and cellular dynamics in lung development and disease. This role involves close collaboration with bench scientists to design experiments, interpret biological data, and translate complex datasets into actionable scientific insights. The bioinformatician will develop and maintain reproducible computational pipelines, generate clear visualizations and reports, and ensure data integrity across all stages of analysis. The position requires both independent problem-solving and active engagement with the broader research team to advance the lab's scientific goals.

Requirements

Master’s degree in Bioinformatics, Biostatistics, Computational Biology, Data Science, Computer Science or related field
Four (4) years of experience analyzing data using high-performance computing
Must successfully pass a drug test through Children’s Hospital Colorado
Must be willing and able to pass a national criminal background check

Nice To Haves

3-5 years of demonstrated experience analyzing large-scale biological datasets, including RNA sequencing (RNA-seq), single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and other multiomics data platforms.
Proficiency in programming and statistical computing, with advanced experience in R and Python, as well as familiarity with reproducible research tools, version control, Docker, and workflow automation.
Strong record of scholarly productivity, including peer-reviewed publications as first author and/or co-author, scientific presentations, and contributions to collaborative research projects.
Experience developing research software, databases, data visualization tools, or web-based applications that support scientific discovery, data management, and communication of research findings to diverse audiences.
Expert knowledge of basic statistical principles relevant in medical research
Expert ability to analyze and solve complex problems and apply quantitative analytical approaches
Demonstrated fluency in one or more programming languages (e.g., R, Python, Perl, Java, C++) and willingness to learn new programming languages as necessary
Familiarity with statistical analytical concepts and methods
Ability to communicate effectively, both in writing and orally

Responsibilities

Design, conduct, and lead independent and collaborative biomedical research projects focused on pulmonary biology, neonatal lung injury, and translational medicine.
Analyze and interpret complex multiomics datasets, including bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics data using R, Python, and advanced bioinformatics methodologies.
Develop, optimize, and maintain reproducible computational workflows utilizing Docker, version control systems, and modern data science best practices.
Perform statistical analyses and generate publication-quality figures, visualizations, and reports to support scientific discoveries and grant-funded research.
Create and deploy interactive data visualization tools and web applications using R Shiny and other software frameworks to facilitate data exploration and scientific communication.
Collaborate with multidisciplinary teams including clinicians, biologists, statisticians, and computational scientists to develop innovative research approaches and translate findings into impactful publications.
Lead manuscript preparation, scientific writing, and presentation of research findings at institutional, national, and international scientific meetings.
Contribute to the development of grant proposals, research protocols, and scientific reports supporting funded research programs.
Mentor students, trainees, research staff, and junior investigators in experimental design, bioinformatics, statistical analysis, and computational research methodologies.
Develop and maintain laboratory databases, data management systems, and data governance practices to ensure data integrity, accessibility, and regulatory compliance.
Apply machine learning, data science, and computational biology techniques to investigate biological mechanisms and identify novel therapeutic targets.
Support the design and implementation of laboratory informatics solutions, including database architecture, workflow automation, and user-centered software development.
Establish standard operating procedures (SOPs) and quality assurance practices to enhance research rigor, reproducibility, and operational efficiency.
Serve as a subject matter expert in computational biology and bioinformatics, providing consultation on study design, data analysis, and interpretation of high-dimensional biological datasets.
Foster scientific collaborations across academic and clinical research programs to advance translational and precision medicine initiatives.
Maintain awareness of emerging technologies, computational methods, and scientific literature to drive innovation and continuous improvement in research programs.
Publish peer-reviewed research findings as first author and co-author in high-impact scientific journals.
Contribute to institutional teaching, training activities, and educational programs related to bioinformatics, data science, computational biology, and biomedical research.