Perform comprehensive computational analyses of single-cell and spatial transcriptomics datasets to characterize the tumor microenvironment in bladder cancer.
Apply advanced statistical and machine-learning methods to identify biomarkers, immune cell states, and biological mechanisms associated with BCG immunotherapy response.
Integrate multi-modal datasets, including scRNA-seq, spatial transcriptomics, bulk RNA-seq, proteomics, and clinical metadata, to achieve a systems-level understanding of tumor–immune interactions.
Incorporate imaging and pathological covariates alongside molecular data to generate clinically interpretable insights and inform treatment strategies.
Lead the synthesis of computational findings into clear, compelling scientific narratives and drive manuscript preparation for submission to high-impact journals.
Collaborate closely with experimental scientists and clinical teams to interpret results, refine hypotheses, and guide translational research directions.
Present findings internally and externally at scientific meetings and seminars.

Requirements

PhD in Computational Biology, Bioinformatics, Data Science, Systems Biology, Biostatistics, or a related quantitative discipline.
Strong experience analyzing high-dimensional omics data (e.g., single-cell RNA-seq, spatial transcriptomics, bulk RNA-seq).
Proficiency in computational programming languages such as R and/or Python.
Demonstrated ability to work independently on complex data analysis projects and communicate results clearly.
Strong scientific writing skills and a track record for first-author publications.
Experience with tumor immunology, cancer biology, or immunotherapy datasets (preferred).
Familiarity with spatial transcriptomics platforms and/or imaging-based analyses (preferred).
Experience integrating multi-modal molecular and clinical datasets (preferred).
Prior exposure to translational or clinically oriented research environments (preferred).

Benefits

Subject to the terms of their respective plans, employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits: Vacation –120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
Holiday pay, including Floating Holidays –13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave – 80 hours in a 52-week rolling period
10 days Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

computational analysissingle-cell RNA-seqspatial transcriptomicsbulk RNA-seqproteomicsstatistical methodsmachine learningdata integrationhigh-dimensional omics datascientific writing

Soft Skills

independent workcommunicationcollaborationhypothesis refinementnarrative synthesispresentation skills

Certifications

PhD in Computational BiologyPhD in BioinformaticsPhD in Data SciencePhD in Systems BiologyPhD in Biostatistics