Career Center

Cancer Early Detection Advanced Research (CEDAR) center is a collaborative institution within the OHSU Knight Cancer Institute. The Knight Cancer Institute, known as one of the pioneers in personalized cancer medicine, is an international leader in research and cancer treatment. At CEDAR our mission is to detect and stop lethal cancers at the earliest stage because early detection saves lives. This is an ambitious goal, one that requires novelty, creativity, and innovation. We are composed of biologists, chemists, biomedical engineers, computationalists, and clinicians conducting groundbreaking translational cancer research to help people maintain a high quality of life and reduce cancer mortality, to create a global early detection community, and to have a positive impact on the Oregon economy.

CEDAR is committed to increasing the diversity of the campus community. We at CEDAR are dedicated to promoting inclusion and multiculturalism to build a successful organization by having outstanding researchers of diverse backgrounds work together on multiple projects. We encourage high-risk, high-reward research projects because defeating cancer requires unproven, out-of-the-box thinking. Our research is milestone driven to ensure that each project is fulfilling its stated goals.

CEDAR funds its own research projects, expediting the process of discovery. Our research is milestone-driven to ensure that each project is fulfilling its stated goals.

Every Knight Cancer employee is expected to embody our guiding principles:

• We act BOLDLYBreakthroughs require pushing the boundaries of science, exploring new frontiers, and thinking differently
• We SUPPORT each otherRespect leads to trust, which leads to excellence
• We work as a CONNECTED teamWe must leverage our collective brain power to conquer cancer because no one individual can do it alone

Our focus on early detection requires novel approaches to reliably identify small/rare signals in diverse data types, with an emphasis on minimally invasive sampling techniques. In this role you would work project teams that include CEDAR scientists such as Gurkan Yardimci, Hisham Mohammed, Andrew Adey and Xiaolin Nan initially and with increasing collaboration over time: We are currently hiring at the level of Computational Biologist 3 with expertise in Computational Biology to work in the following areas:

• Machine Learning/Statistics Developing machine learning methods and/or statistical models to study the organization of the epigenome and three dimensional structure of the genome using cutting edge genomics and super resolution microscopy datasets. Developed algorithms will be used to deeply characterize cell populations and identify features that are indicative of cell state. Techniques such as (but not limited to) dimensionality reduction, clustering, and predictive modeling will be utilized.
• Genomics/single cell genomics Modeling and analyzing next-generation sequencing datasets that measure the transcriptome and the epigenome, with an emphasis on the single-cell variants, such as single cell RNA-seq and single cell ATAC-seq. The successful candidate will use both existing tools and develop their own computational methods to analyze such datasets for characterization of healthy and cancerous cell populations.
• Multiomics Developing computational methods for the analysis of single-cell multiomics technologies that are able to characterize multiple omes of a single cell concurrently, such as the epigenome and the transcriptome (see references below). These methods will be utilized for deep characterization of healthy and cancerous cells and investigate the links between the transcriptome, the epigenome and 3D conformation of chromatin.

Select references:

• https://www.nature.com/articles/s41586-019-1825-8
• https://www.nature.com/articles/nbt.4112
• https://science.sciencemag.org/content/361/6409/1380
• https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008173

Duties Include:

• Team Science: Collaborate on teams and/or lead teams on the identification of scientific problem, design of approach to address it, and identification, acquisition and management of resources to perform investigations. Foster and support teamwork. Provide training and guidance to fellow researchers and staff.
• Laboratory Research Project Management: Independently develop and manage research experiments, determining the most suitable methods to be used. Interpret and perform complex data analysis on experimental results and determine whether they are consistent with goals. Ensure that research team members maintain accurate and detailed records of all experimental procedures, data collections and analysis performed. Maintain a high level of professional expertise through familiarity with current scientific literature. As needed, develop innovative techniques and experimental systems to meet research program goals.
• Scientific Writing and Project Proposal Development: Prepare research findings for presentation at scientific meetings and conference and manuscripts for publication. Prepare research project proposals for internal review, prepare annual or bi-annual research progress summaries and presentations for CEDAR scientists and staff.
• Laboratory Organization and Compliance: Develop and implement procedures and systems to maximize the organization and efficiency within designated projects. Mentor and train lab members on lab practices and protocols. Ensure that staff is adequately trained to meet compliance for regulatory board reviews as required. Aid in the submission of specific protocols to the Institutional Review Board and other regulatory review boards.
• Collaborative Interactions: Develop, foster and maintain relationships with partners in academia and in the pharmaceutical/biotechnology industries.

• PhD in Computational Biology or related field OR Master's Degree in Computational Biology or related field AND 6 years of relevant experience OR Equivalent combination of training and experience
• Those with a Master's Degree in Computational Biology or related field AND 3 years of relevant experience OR Bachelor's Degree in Computational Biology or related field AND 6 years of relevant experience OR Equivalent combination of training and experience will be considered at the Research Associate level
• Major coursework in the one of the following ares: computational biology, statistics, computer science or machine learning
• Programming experience with python/R or equivalent programming languages
• Experience in working with existing software for the analysis of next generation sequencing genomics data such as RNA-seq, ATAC-seq and Hi-C, including their single-cell versions
• Strong background in machine learning or statistics
• Excellent communication, analytical and organizational skills
• Ability to work independently and as part of a team while being collaborative in resolving problems
• Satisfactory publication record
• Demonstrated ability to learn new and innovative processes quickly
• Must possess energy and drive to coordinate multiple projects simultaneously
• Ability to use tact and diplomacy to maintain effective working relationships

• PhD and 2+ years of experience, MS and 5+ years of experience, or BS and 10+ years of experience
• Background in one and more of following topics: mixture modeling, deep learning, dimensionality reduction
• Track record of developing computational methods for modeling and analyzing genomics datasets
• Ability to clearly communicate and collaborate with researchers from diverse backgrounds, including wet-lab scientists
• Expertise in early cancer detection
• Experience in a collaborative or team science based environment
• Experience in user friendly software development, maintenance , and version control

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

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