Key Dates

NOT-CA-22-097 - Notice of Intent to Publish a Funding Opportunity Announcement for NCI Pathway to Independence Award for Outstanding Early Stage Postdoctoral Researchers (K99/R00 - Independent Clinical Trial Required)

NOT-CA-22-098 - Notice of Intent to Publish a Funding Opportunity Announcement for NCI Pathway to Independence Award for Outstanding Early Stage Postdoctoral Researchers (K99/R00 - Independent Basic Experimental Studies with Humans Required)

RFA-CA-21-060 - NCI Pathway to Independence Award for Outstanding Early Stage Postdoctoral Researchers (K99/R00 - Independent Clinical Trial Not Allowed)

National Cancer Institute (NCI)

The National Cancer Institute (NCI) intends to reissue a Funding Opportunity Announcement (FOA) to facilitate a timely transition of outstanding early stage postdoctoral researchers from their mentored, postdoctoral research positions to independent tenure-track (or equivalent) faculty positions. The program will provide independent NCI research support during this transition to help awardees to launch competitive, independent research careers. Researchers in the scientific areas of data science and cancer control science are especially encouraged to apply.

The FOA is intended to be a re-issuance of RFA-CA-21-060.

This FOA will utilize the K99/R00 Career Transition Award/Research Transition Award.

This Notice is being provided to allow sufficient time for institutions to nominate candidates and for applicants to develop strong applications.

Details of the planned FOA are provided below.

This Notice encourages outstanding early stage postdoctoral researchers, especially in the scientific areas of Data Science and Cancer Control Science (as defined below) to begin to consider applying for these reissued FOAs. This K99/R00 award is intended for individuals who require no more than 2 additional years of mentored research training and career development (K99 phase) before transitioning to the independent stage (R00 phase) of the program. Consequently, the strongest applicants will require and will propose, a well-conceived plan for 1–2 years of substantive mentored research training and career development that will help them become competitive candidates for tenure-track faculty positions and prepare them to launch robust, independent research programs. The early stage K99/R00 candidates must have no more than 2 years of postdoctoral research experience as of the relevant application due date. Individuals must be in mentored, postdoctoral training positions to be eligible to apply to the K99/R00 program. If a candidate achieves independence (i.e., any faculty or non-mentored research position) before a K99 award is made, neither the K99 award nor the R00 award, will be issued. Each candidate must be nominated by the applicant institution. Each eligible institution (defined as having a unique entity identifier (UEI) or an Institutional Profile File (IPF) number may submit up to a combined total of three applications (one in Data Science, one in Cancer Control Science, and one in Other Sciences as defined below) to any companion RFA or any combination of companion RFAs. The institutional nomination letter must be written and signed by the head of the candidate's postdoctoral department or program. The letter must identify one of the three scientific areas as the candidate's proposed research area of expertise and must affirm that the candidate is the institution's sole nominee in this scientific area for the specified application due date. It should affirm the candidate's near-readiness to transition to independence and describe the main factors that identify the nominee as likely to obtain a tenure-track or equivalent research position at an early career stage. For the purpose of this award the scientific areas are defined as follows:

• (A) Data Science: For the purposes of this K99/R00 award, data science is defined as an interdisciplinary field of inquiry in which quantitative and analytical approaches, processes, and systems are both developed and used to extract knowledge and insights from increasingly large and/or complex sets of data. This includes cancer-focused data integration and visualization, systems biology, artificial intelligence, machine learning, informatics, genomics, precision oncology, and developing analytics for epidemiological or biostatistical studies.
• (B) Cancer Control Science: For the purposes of this K99/R00 award, cancer control science is defined as basic and applied research in the behavioral, social, and population sciences to create or enhance interventions that, independently or in combination with biomedical approaches, reduce cancer risk, incidence, morbidity, and mortality, and improve quality of life. This includes research in epidemiology, behavioral sciences, health services, surveillance, cancer survivorship, and healthcare policy.
• (C) Other Sciences: For the purposes of this K99/R00 award, "Other Sciences" includes all scientific fields supported by the NCI that are not included in (A) or (B). Applicants proposing research in (C) "Other Sciences" may apply only if it is reasonable to expect them to transition to independence with an abbreviated period of mentored research training beyond their original doctoral degrees.

Pre-Application Webinar: The NCI anticipates holding a pre-application webinar (tentatively in mid-November 2022) to which all interested prospective applicants, mentors, administrators, and grant managers are invited. An NCI program director will explain the goals and objectives of the NCI Pathway to Independence Award for Outstanding Early Stage Postdoctoral Researchers, discuss the eligibility and nomination requirements, explain the application peer review process, and answer questions. Information about the pre-application webinar will be available after the publication of the FOA under the "NCI Early K99 Award" tab of the NCI Cancer Training Branch website.

TBD

Applications are not being solicited at this time. 

Please direct all inquiries to:

Sergey Radaev, Ph.D.

National Cancer Institute (NCI)

240-276-5630

[email protected]