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. CEDAR offers a unique opportunity for outstanding, driven, and creative postdoctoral fellows to perform cutting edge and high-risk research, ranging from understanding basic cancer biology to developing novel technologies to aid detection. 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.

The OHSU Fellowship for Diversity in Research seeks to address the need for increased representation of minoritized races/ethnicities in STEM at the postdoctoral level. Eligible candidates are encouraged to apply. Visit www.ohsu.edu/ofdir for more information.

We are currently hiring for 1-2 highly motivated fellows with expertise in Computational Biology to work in the following areas. Candidate would work with CEDAR and OHSU scientists including Gurkan Yardimci, Hisham Mohammed, Andrew Adey and Xiaolin Nan initially and with increasing collaborations over time:

• 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.

• Imaging Performing analysis of existing genomics data of cancerous cells to aid the design of super high resolution microscopy experiments for imaging the chromatin organization of cancerous cells. The successful candidate will have the opportunity to analyze cutting edge super high resolution microscopy experiments and develop computational methods for joint analysis of genomics and imaging data.

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://www.nature.com/articles/s41467-020-18181-6
• https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008173

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 team We must leverage our collective brain power to conquer cancer because no one individual can do it alone

Duties Include:

• Prepare manuscripts, and present research findings as abstracts or oral presentations (travel may be required)
• Attend weekly group meetings and 1:1 meetings to: 1) present data and interpretation of results; 2) troubleshoot research results and 3) suggest next steps
• Attend research related meetings including but not limited to Thursday PM SPORE seminars, Cancer Biology meetings, journal clubs
• Perform experiments utilizing appropriate lab or computational techniques with proficiency, evaluate results, and determine the next steps to complete project and present data. Think independently and problem solve. Stay on top of the literature and build skills to maximize the projects potential.
• Duties as assigned

• PhD witha minimum of 3 years as a graduate student
• Specialty: computational biology, statistics, computer science or machine learning
• Excellent communication, analytical and organizational skills
• Ability to work independently and as part of a team while being collaborative in resolving problems
• Passion for science and inquiry
• Ability to synthesize ones own results and others to formulate hypotheses
• Energy and drive to coordinate multiple projects simultaneously

• Programming experience with python/R
• Background in one and more of following topics: mixture models, deep learning, dimensionality reduction
• 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
• Experience in developing computational approaches for modeling genomics data
• Ability to clearly communicate and collaborate with researchers from diverse backgrounds, including wet-lab scientists

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

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