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Fred Hutch · 20 hours ago

Staff Scientist

Seattle, WA

Full-time

Onsite

Senior Level, Lead/Staff

$84K/yr - $192K/yr

3+ years exp

Fred Hutchinson Cancer Center is an independent, nonprofit organization focused on cancer and infectious diseases. The Staff Scientist position involves conducting independent research, developing assays for cancer diagnostics, and collaborating with interdisciplinary teams to advance the understanding of cancer genomics and epigenetics.

Hospital & Health Care

No H1B

Responsibilities

Conduct research independently as well as contribute to research being done by other team members

Assist in project development, design, and management

Participate in the training of undergraduate, graduate, and postdoctoral scientists

Lead mining and integration of large-scale multi-omic datasets (WGS, methylation, chromatin, cfDNA) to identify quantitative biomarkers for ctDNA detection and tumor characterization

Develop, refine, and benchmark computational pipelines for biomarker selection using statistical modeling, machine learning, and deep learning approaches

Build robust cloud-based workflows and scalable pipelines for large-scale genomic data processing

Innovate and evaluate new metrics for ctDNA quantification (e.g., methylation-based signals, fragmentation, gene expression inference)

Design and optimize ctDNA assays using low-cost molecular platforms such as low-pass WGS, EM-seq, targeted sequencing, ddPCR and others

Translate computational biomarkers into practical assays via targeted primer/panel design, reaction optimization, and QC framework development

Conduct analytical validation studies including LOD determination, precision, reproducibility, and specificity

Contribute to development of prognostic biomarkers for clinical applications

Collaborate with CLIA/CAP laboratory teams to integrate assay workflows into clinical pipelines, including documentation for LDT deployment

Support translational studies in collaboration with clinicians and academic/industry partners (e.g., tumor detection, subtyping, therapeutic stratification)

Lead validation efforts on real-world biospecimens such as plasma

Qualification

PhDMD in biomedical scienceLiquid biopsy assay developmentLarge-scale genomic data analysisMachine learning modelsProgramming in RPythonNGS-based assaysAssay optimizationCtDNA biology understandingCollaboration with cliniciansPeer-reviewed publicationsCommunication skills

Required

A PhD and/or MD degree in a biomedical science discipline such as biology, molecular biology, biochemistry, biophysics, computer science, computational biology, biostatistics, biomedical engineering, or other related fields

Experience and expertise with programming languages and environments such as R, Python, others

Demonstrated experience in liquid biopsy assay development (cfDNA/ctDNA)

Hands-on experience with NGS-based assays, including epigenetic assays such as cfDNA methylation sequencing

Strong background in processing and analyzing large-scale genomic datasets (WGS, methylation, cfDNA fragmentation, variant calling)

Significant experience with Python, R, and workflow managers (bash, Snakemake, Nextflow)

Expertise developing machine learning and deep learning models

Experience with assay optimization and analytical validation (LOD, specificity, reproducibility)

Understanding of ctDNA biology, cfDNA fragmentation, tumor heterogeneity, and multi-omic biomarker design

Ability to interpret complex biological results and communicate them clearly

Publications of peer reviewed articles in the field of genomics, genetics, cell engineering, or developmental biology

A minimum of 3 years of direct experience in molecular biology, developmental biology, genetics, epigenetics, computational genomics, or related fields