Postdoctoral Research Scientist in viral evolution, genomics, and mathematical modeling. Columbia University Medical Center

The Rabadan Lab is a multi-disciplinary team at the Columbia University Medical Center consisting of computational and evolutionary biologists, applied mathematicians, physicists, and physicians. As part of the Departments of Systems Biology and Biomedical Informatics, we collaborate with clinicians and public health researchers from around the world to explore the genetic underpinnings and epidemiology of infectious diseases and cancer. As part of the Center for Topology of Cancer Evolution and Heterogeneity, we are building a vibrant community of researchers who use insights and techniques from computational topology to solve pressing biomedical problems.

We are seeking a postdoctoral researcher who wants to work in a creative and collaborative environment on new mathematical approaches for understanding viral evolution.

Candidate qualifications include:

  •  PhD in any quantitative science (preferably mathematics, computer science, physics, astrophysics, computational biology, statistics, or engineering) or in life sciences with strong focus on mathematical modeling, evolution, and/or computation.
  • Expertise in high-throughput sequencing technologies is highly valued.
  • Excellent organizational and communication skills are a must.

Application Process:

Please send the following to st3090@cumc.columbia.edu

  1. Cover letter, highlighting experience with quantitative methods for understanding biological data and evolutionary processes
  2. CV
  3. Names and contact information for three references

Columbia University is an affirmative action/equal opportunity employer and encourages applications from women and underrepresented minorities.

Funding opportunities for interdisciplinary research from the Center for Topology of Cancer Evolution and Heterogeneity

The Columbia University Center for Topology of Cancer Evolution and Heterogeneity is an interdisciplinary center formed to develop an integrated experimental and computational approach for characterizing tumor evolution within solid tumors.

Clonal evolution and tumor heterogeneity are believed to play key roles in generating patient-specific variations in cancer phenotype and in the emergence of resistance to treatment during disease progression. Due to difficulties in performing longitudinal assessments and limitations in identifying the cell(s) of origin, the process of clonal evolution in solid tumors (such as prostate and brain cancers) is not well understood.  The Center, as part of the National Cancer Institute’s Physical Sciences in Oncology Network, will employ novel experimental techniques such as multi-color organoid systems for tracing cellular lineages, as well as innovative single-cell sequencing technologies. We are combining these methods with emerging approaches from topological data analysis that are well suited to analyzing the high-dimensional data that single-cell approaches generate.

The Center has announced its opening call for proposals for pilot grants. These grants are intended to facilitate collaborations between mathematicians/physicists and cancer researchers that will lead to innovative new applications for the analysis of large biological data sets. This year’s round of funding will support five projects, including:

  • one pilot grant of $40,000 to support technology development and/or research involving wet lab experimentation
  • four collaborative grants of $10,000 each to support mathematical/computational research in collaboration with the Center. Collaborations are required to involve at least one researcher within the Center.

The goal of the program is to foster the development of new technologies and quantitative methods for the analysis of cancer genomic data. All applications must demonstrate close interdisciplinary collaboration between quantitative scientists and cancer biologists. Pilot projects and collaborative grants will enable the development and testing of new mathematical approaches within the context of cancer research, give mathematicians and physicists experience working in biological settings, and provide cancer biologists opportunities to explore how mathematical methods can be used to guide research agendas.

More information about the center and proposal requirements and deadlines can be found in the following link.

Postdoctoral Research Scientist, Columbia University Medical Center

We are searching for a postdoctoral researcher commencing spring / summer 2016.

The Rabadan Lab (rabadan.c2b2.columbia.edu) is a multi-disciplinary team at the Columbia University Medical Center consisting of applied mathematicians, computational and evolutionary biologists, physicists, and physicians. As part of the Center for Topology of Cancer Evolution and Heterogeneity, we are building a vibrant community of researchers who use insights and techniques from computational topology to solve pressing biomedical problems. Research topics include:

  • How does HIV evolve and adapt within the host environment? Evolutionary trees may not be the best way to understand and visualize a viral population that recombines, draws upon a reservoir of archival virus, and starts and stops replicating in response to changes in treatment. Major decisions about the direction of HIV cure research are being made on the basis of evolutionary studies, and building accurate analytical tools for these studies is a priority. What topological structures, other than trees, can help us understand and communicate viral evolution?
  • How do tumors diversify as they develop? Single-cell and deep sequencing of tumors have revealed considerable heterogeneity in both solid and blood tumors. Therapies targeted to single genes that are mutated in only one part of the tumor – even the largest part of it – may fail to eradicate the entire disease. We are using methods of computational topology to visualize and analyze the genetic and transcriptomic relationships between different parts of tumors.

We are searching for a postdoctoral researcher who wants to work in a creative and collaborative environment on these and other questions related to human health and evolution, carcinogenesis, and microbial pathogens. Candidate qualifications include:

  • PhD in Mathematics, Applied Mathematics, or a computational science;
  • Experience building tools for computational topology and visualization of complex data;
  • Experience and/or demonstrated interest in biological and/or clinical questions;
  • Strong programming background and interest in building tools for the broader research community.

Candidates with only some of the above qualifications are also highly encouraged to apply – we are always looking for talented and dedicated pre- and post-doctoral scientists!

Application Process

Option 1: Please send CV and one or two relevant publications/pre-prints to me at dsr2131@columbia.edu. In your email, please highlight any important aspects of your experience. Recommendations/references are not necessary in your initial email, but may be requested for follow-up. I look forward to hearing from you!

Option 2: Follow instructions at

http://academicjobs.columbia.edu/applicants/Central?quickFind=62376

Best wishes,

Daniel Scholes Rosenbloom

Equal Opportunity Employment

Columbia University is an Equal Opportunity and Affirmative Action employer – Race/Gender/Disability/Veterans. It is committed to a workforce of faculty and staff that reflects the diversity and talent of New York City, the larger metropolitan area, and the nation. It is also committed to a working and learning environment supportive of its faculty and staff in their pursuit of productive and fulfilling professional and personal lives. See eoaa.columbia.edu for more information.

Local Hiring

Columbia University is committed to the hiring of qualified local residents.

Disability Accommodations

Columbia University provides reasonable accommodations to qualified individuals with disabilities who can perform the essential functions of the position. If you need a reasonable accommodation for any part of the application and hiring process, please notify: Manager of Return to Work Program, Office of Human Resources, at hrdisability@columbia.edu. Decisions on granting reasonable accommodation will be made on a case-by-case basis.

Funding opportunities for interdisciplinary research from the Center for Topology of Cancer Evolution and Heterogeneity

The Columbia University Center for Topology of Cancer Evolution and Heterogeneity has opened in May 2015 as an interdisciplinary center formed to develop an integrated experimental and computational approach for characterizing tumor evolution within solid tumors.

Clonal evolution and tumor heterogeneity are believed to play key roles in generating patient-specific variations in cancer phenotype and in the emergence of resistance to treatment during disease progression. Due to difficulties in performing longitudinal assessments and limitations in identifying the cell(s) of origin, the process of clonal evolution in solid tumors (such as prostate and brain cancers) is not well understood.  The Center, as part of the National Cancer Institute’s Physical Sciences in Oncology Network, will employ novel experimental techniques such as multi-color organoid systems for tracing cellular lineages, as well as innovative single-cell sequencing technologies. We are combining these methods with emerging approaches from topological data analysis that are well suited to analyzing the high-dimensional data that single-cell approaches generate.

The Center has announced its opening call for proposals for pilot grants. These grants are intended to facilitate collaborations between mathematicians/physicists and cancer researchers that will lead to innovative new applications for the analysis of large biological data sets. This year’s round of funding will support three projects, including:

  • one grant of $40,000 to support technology development and/or research involving wet lab experimentation
  • two grants of $20,000 each to support mathematical/computational research

The goal of this pilot grant program is to foster the development of new technologies and quantitative methods for the analysis of cancer genomic data. All applications must demonstrate close interdisciplinary collaboration between quantitative scientists and cancer biologists.

More information about the center and proposal requirements and deadlines can be found in the following link.