Research Assistant - Anatomy and Cell Biology (Ryan Lab) 50%25

University of Iowa•Iowa City, IA

22h•Onsite

About The Position

The Research Assistant – Computational Scientist supports research efforts in Dr. Amy Ryan’s laboratory, which studies lung regeneration and the molecular and cellular mechanisms underlying mucociliary clearance. Under general supervision the position will provide comprehensive computational and data science support across all laboratory projects, with a primary focus on advanced analysis of high-dimensional biological datasets, including bulk and single-cell RNA sequencing, epigenomics, proteomics, and multimodal data integration. This role involves the development, implementation, and maintenance of computational pipelines; application of statistical and machine learning methodologies; and generation of integrative models of mucociliary function in lung health and disease. The Research Assistant collaborates closely with experimental scientists, trainees, and collaborators, contributing to study design, data interpretation, visualization, and dissemination. The position may also support data infrastructure efforts, including database development, data warehousing, and innovative computational tools that enhance data sharing, reproducibility, and discovery.

Requirements

Bachelor’s degree in computational biology, Bioinformatics, Data Science, Biostatistics, Computer Science, Biomedical Engineering, or a closely related quantitative or life‑science field, or equivalent combination of education and progressively responsible experience in a research laboratory environment.
Experience performing computational analysis of high‑throughput biological data, such as bulk RNA sequencing and/or single‑cell RNA sequencing (scRNA‑seq).
Proficiency in at least one programming language commonly used in computational biology (e.g., R and/or Python).
Working knowledge of standard bioinformatic workflows, including data quality control, normalization, statistical analysis, and data visualization.
Familiarity with at least one additional omics data type (e.g., epigenetic data such as ATAC‑seq, proteomics, or similar large‑scale datasets).
Experience working with large, complex datasets and organizing analysis outputs in a structured and reproducible manner.
Ability to follow established computational pipelines and analytical protocols under general supervision.
Strong attention to detail and ability to document computational methods, code, and results.
Effective written and verbal communication skills, including the ability to explain computational results to collaborators with varied scientific backgrounds.
Ability to work collaboratively as part of a multidisciplinary research team and manage multiple projects simultaneously.

Nice To Haves

Experience with integration of multimodal datasets (e.g., transcriptomic, epigenomic, proteomic, and phenotypic data).
Familiarity with single‑cell analysis frameworks and tools (e.g., Seurat, Monocle, or similar).
Exposure to epigenomic analysis workflows, including chromatin accessibility or regulatory element analysis.
Basic experience applying machine learning or predictive modeling approaches to biological data.
Experience developing or contributing to reproducible workflows using version control systems (e.g., Git).
Experience generating publication‑quality figures and contributing to manuscripts, abstracts, or grant applications.
Interest in lung biology, regenerative medicine, mucociliary clearance, or related biomedical research areas.
Willingness to learn new computational methods and emerging approaches relevant to laboratory research.
Master’s degree in computational biology, Bioinformatics, Data Science, Biostatistics, Computer Science, Biomedical Engineering, or a closely related quantitative or life‑science field.

Responsibilities

Perform computational analyses of biological datasets, including bulk RNA-seq and single-cell RNA-seq (scRNA-seq), following established laboratory and field-standard workflows.
Conduct quality control, normalization, differential expression analysis, clustering, pathway analysis, and data visualization under guidance from senior staff or investigators.
Apply basic to intermediate statistical and machine learning approaches to support modeling of mucociliary clearance mechanisms.
Assist in the integration of multimodal datasets (e.g., transcriptomic, epigenomic, proteomic, and phenotypic data).
Help maintain, adapt, and document computational pipelines and scripts to ensure reproducibility and accuracy.
Generate figures, summaries, and visualizations for manuscripts, presentations, grant applications, and internal reports.
Support development and maintenance of laboratory databases, data repositories, or data warehouse portals as assigned.
Work collaboratively with laboratory members, including faculty, staff, postdoctoral scholars, and trainees, to support data interpretation and experimental planning.
Communicate computational findings clearly to non-computational collaborators.
Assist in preparing documentation of computational methods for publications and regulatory or funding requirements.
Organize, document, and maintain computational data, code, and analysis outputs in accordance with laboratory and institutional standards.
Adhere to data management, security, and responsible conduct of research policies.
Maintain version control and analysis records to support transparency and reproducibility.
Learn and apply new computational and bioinformatic methods relevant to ongoing laboratory projects.
Participate in laboratory meetings and training activities.
Perform other research-related duties as assigned, consistent with the PRK1 classification.