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The Division of Oncological Sciences at OHSU's Knight Cancer Institute focuses on understanding cancer through various research methods. The ultimate goal is to improve cancer prevention, detection, and treatment for everyone. 

The division's research is conducted by a collaborative team of scientists, faculty, trainees, and staff from diverse backgrounds. They work together to turn lab discoveries into real-world benefits for cancer patients and the wider community. Their research is built around teamwork and covers four key areas: Precision Systems Oncology, Cancer Data Science (including computer biology, bioinformatics, and biostatistics), Chemical Biology and Experimental Therapeutics, and Cancer Population Science. A major priority is to understand cell plasticity, which is the ability of cells to change their type or identity. Researchers are particularly interested in how cells transition from normal to cancerous, from cancer to spreading (metastasis), and from metastasis to becoming resistant to treatment.

A Computational Biologist 1 (CB1) position is available to support ongoing work in the lab of Dr. Olga Nikolova in the Division of Oncological Sciences. The Nikolova Lab develops computational methods to understand and model drug response in cancer patients. The CB1 will contribute to a project evaluating computational methods that predict drug response in heterogeneous cell populations.

Under supervision, the CB1 will work to complete an existing project in the lab that aims to publish the first computational benchmark of single-cell omics methods for drug response prediction. The candidate will design and maintain software pipelines for evaluation of computational approaches and downstream analysis of their results. The candidate must have experience working with omic data and single-cell RNA-sequencing transcriptomic data. The candidate must also have demonstrated fluency in R and python as well as building pipelines using bash scripting and snakemake-like approaches. Expertise including RStudio, Shiny framework, GitHub code version control, Seurat, DESeq2, and have experience with bulk and single-cell dataset analysis workflows including data normalization, dimensionality reduction, and clustering. The candidate should be skilled in biological pathway analysis tools (e.g., GSEA, IPA) and visualizations (e.g., R, Cytoscape) and have experience with interpretation of computational analysis results. The candidate will be a highly communicative team player able to coordinate with the team in goal setting, milestone completion and generation of publication-ready figures to support manuscripts, grants and publications. Candidate will be expected to drive the completion of a scientific publications summarizing the findings of the benchmark project.

• Master's Degree in Computational Biology or related field OR Bachelor's Degree in Computational Biology or related field AND 3 years of relevant experience
• Demonstrated proficiency with data analysis and bulk and single-cell RNA-seq workflows, including quality control, normalization, differential expression analysis, dimensionality reduction, clustering, or cell-state analysis.
• Sustained experience working and communicating effectively within an interdisciplinary collaborative team with wet-lab scientists and computational biologists.
• Demonstrated experience generating clear data visualizations and publication-quality figures for manuscripts, grants, and presentations.
• Proficiency in R, Python, and Bash, with experience using relevant tools such as RStudio, Seurat, DESeq2, FastQC.
• Demonstrated skills in biological pathways analysis and visualization (GSEA, IPA, Cytoscape) and interpretation of omic datasets.
• Demonstrated ability to organize, present and interpret results from computational analysis.
• Track record of effective collaboration with wet-lab scientists.
• Track record of maintaining organized, reproducible, and well-documented analysis workflows.
• Demonstrated ability to communicate computational methods and results through writing and publication-ready figures for manuscripts, grants, and presentations.

• Master’s Degree in Computational Biology AND 2 years of relevant experience
• Knowledge of tumor imaging analysis and tools such as QuPath, Living Image, and MCMICRO.

Apply online. Please be sure to upload a Cover Letter and Resume/CV.

 

We offer a variety of benefits on top of joining a thriving organization:

• Medical, dental and vision coverage at no or low cost to employees
  • Covered 100% for full-time employees and 88% for dependents
• Several retirement plans to choose from with contributions from OHSU
• 25 days a year of paid time off
• 8 days of sick time off
• Commuter subsidies
• Tuition reimbursement
• Access to group life insurance, disability insurance and other supplemental benefits
• Annual Merit Increase
• Growth/Development Opportunities
• Employee discounts to local and major businesses

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We are Oregon's only public academic health center.
In addition to caring for patients, we lead groundbreaking research. We also train the next generation of health care professionals. As Portland's largest employer, we give you opportunities to learn and advance in a system of hospitals and clinics across Oregon and Southwest Washington.
All are welcome.
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To request reasonable accommodation, contact askhr@ohsu.edu