Bioinformatics Research Scientist

University of Florida•Gainesville, FL

1d•Onsite

About The Position

The University of Florida Health Cancer Institute (UFHCI) invites applications for a master’s-level bioinformatics research scientist in its Biostatistics and Computational Biology Shared Resource (BCB-SR). The position reports to the Associate Director for Cancer Quantitative Sciences and Director of the BCB-SR, and works within the Bioinformatics Unit alongside biostatisticians and computational scientists. The unit provides analytical support to UFHCI members. The successful candidate will collaborate directly with cancer researchers from experimental design through analysis, interpretation, and publication. The role involves a broad and changing project portfolio, substantial investigator contact, and regular co-authorship on peer-reviewed publications. The position supports cancer research through high-throughput genomics analysis, consultation on study design and analysis plans, development and maintenance of reproducible computational workflows, and integration of multi-omic, clinical, and public data. The scientist will interpret findings with investigators and contribute to grant applications, publications, presentations, training, and shared-resource operations. The role is a professional position for candidates with advanced training, education, and experience in bioinformatics, computational biology, or related fields. It is not a remote position and is located on the University of Florida’s Main Campus in Gainesville, Florida.

Requirements

Master’s degree in bioinformatics, computational biology, genetics, molecular biology, computer science, or a closely related field.
Demonstrated experience analyzing high-throughput sequencing data, evidenced by publications, preprints, dissertation work, or a public code portfolio.
Proficiency in R and/or Python.
Working knowledge of the Linux command line and shell scripting.
Strong written and verbal communication skills.
Ability to work effectively with a broad range of collaborators, including investigators, trainees, industry sponsors, partners at other institutions, and UFHCI staff.
A bachelor’s degree in an appropriate area of specialization and two years of experience, as stated in the classification minimum requirements.

Nice To Haves

Experience in a shared resource or other collaborative setting managing multiple concurrent projects and deadlines.
Experience with high-performance computing environments and job schedulers such as SLURM.
Experience with workflow systems such as Nextflow, Snakemake, or WDL; containerization tools such as Apptainer/Singularity or Docker; and version control such as Git.
Experience with single-cell and spatial transcriptomics analysis.
Working knowledge of applied statistics relevant to genomics, including generalized linear models, mixed models, multiple testing correction, and multi-omic integration.
Familiarity with public data resources and repositories such as TCGA, GTEx, ENCODE, GEO/SRA, and dbGaP.
Experience with compiled languages such as C++ or Rust, SQL, or relational database design.
Experience developing and releasing software packages through Bioconductor, CRAN, PyPI, or equivalent.
Experience contributing to federal grant applications.
Familiarity with handling protected health information and controlled-access data under HIPAA and dbGaP data use agreements.

Responsibilities

Analyze high-throughput genomics data for UFHCI investigators, including bulk and single-cell RNA-seq, ATAC-seq, DNA methylation assays (WGBS, EM-seq, RRBS), ChIP-seq, and whole-genome or whole-exome sequencing.
Consult with investigators on experimental design, feasibility, and analysis plans before data are generated.
Contribute analysis plans, preliminary data, and written text to grant applications.
Develop, adapt, and maintain reproducible analysis pipelines and software on UF’s HiPerGator high-performance computing cluster using workflow managers, containers, and version control.
Integrate multi-omic, clinical, and publicly available data sets, and develop or adapt statistical and computational methods when existing tools are inadequate.
Interpret results in collaboration with investigators and contribute figures, methods sections, and manuscript text to publications and presentations.
Maintain organized project documentation, code repositories, and data management practices.
Track service requests and effort for shared-resource reporting.
Contribute to training and outreach for cancer center members and trainees, including workshops, tutorials, and individual instruction.
Maintain current knowledge through seminars, journal clubs, and scientific meetings, and evaluate emerging methods and tools for adoption by the unit.