Call for Participation:
OSEEER Early Career Mentoring (ECM) Program

Updated 12 May 2020

The Operations and Systems Engineering Extreme Event Research (OSEEER) network, supported by the National Science Foundation, is calling for participation in an Early Career Mentoring (ECM) program for pre-tenure, tenure-track faculty in Operations Engineering (OE). The objective of the ECM program is to create and train a network of early career researchers working within and across OE-centered areas in order to address high-impact, methodologically challenging problems in the broad area of hazards and disasters.

The need to provide decisional guidance in the hazards and disaster domain requires a renewed focus on fundamental advances and discoveries within and across three main areas: methods for identifying and defining potentially high-impact research problems; techniques for addressing these problems through a combination of analytic modeling, data-driven approaches, and advanced technologies; and scientifically grounded techniques for supporting decision making through the use of these techniques.

OSEEER ECM is a one-year mentoring program in which each faculty Fellow is paired with a senior scholar Mentor in order to support the Fellow’s professional development. Activities include ongoing discussions of potential research topics; participation in tutorials and in discussions concerning the development of proposals and publications; career development; and participation in ECM-wide meetings to share insights and best practices. Given ongoing travel restrictions due to COVID-19, we anticipate that some activities and meetings will take place via teleconference. OSEEER ECM builds on the tradition of NSF’s ENABLING program, and indeed includes a number of past participants in that program.

Eligible applicants must be tenure-track Assistant Professors (as of Fall 2020) at universities in the United States and have not yet attained tenure and promotion. Applicants should be (or plan to be) conducting research in and/or across OE-related areas, including but not limited to Operations Research, Risk Analysis, and Human Factors. We seek applications from faculty in academic departments with doctoral programs, as well as from those within non-doctoral programs who have demonstrated a commitment to research-intensive careers. OSEEER ECM has a strong commitment to diversity in all aspects, and therefore strongly encourages applications from members of under-represented groups, as well as the inclusion of topical areas which address diversity in the context of hazards and disasters. Our goal is to recruit promising junior scholars who will in turn strive to develop a diverse and vibrant community of OE scholars.

The following materials are all required.
1. A current curriculum vitae
2. A one-page statement of significant research beyond the dissertation
3. A one-page statement of current research and teaching activities
4. Two letters of recommendation from scholars external to the applicant’s tenure-track institution.

Applications are due on or before Monday, June 15, 2020. Approximately six fellows will be selected through a competitive application process. Items 1-3 should be sent to Laura Albert as a single PDF file. Letters (Item 4) should also be submitted as PDF files emailed by the recommender to Dr. Albert. Include the candidate's last name in the file name. Dr. Albert's contact information is below.

The OSEEER ECM Mentors include
Laura Albert, University of Wisconsin-Madison
Robin Dillon-Merrill, Georgetown University
Royce Francis, George Washington University
Erica Gralla, George Washington University
Seth Guikema, University of Michigan
Maria Mayorga, North Carolina State University
David Mendonça, Rensselaer Polytechnic Institute
David Woods, The Ohio State University

Questions about OSEEER ECM should be directed to Laura Albert, University of Wisconsin-Madison. Email:

Questions about OSEEER in general should be directed to the project PI, David Mendonça, Rensselaer Polytechnic Institute. Email:

Statement of Support
This material is based upon work supported by the National Science Foundation under Grant No. 1936967.

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