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Job no: 525096
Work type: Research Faculty
Senior management: College of Engineering
Department: Industrial and Systems Engineering
Location: Falls Church, Virginia
Categories: Engineering, Research / Scientific
Applications are invited for a National Science Foundation funded (LEAP‑HI Program #2051685), Postdoctoral Associate position with the System Performance Laboratory (SPL) in the Grado Department of Industrial and Systems Engineering, Virginia Tech. The position will be located at the Virginia Tech Northern Virginia Center in Falls Church, VA. The desired duration of the position is 1+1 (optional years if mutually desired), totaling up to two calendar years. The candidate will conduct research and mentoring duties, in addition to optional teaching of one course per year, if mutually desired. Research will focus on multi-level investigation of safety-critical human-in-the-loop systems that collaborate with automated/autonomous decision-aid technologies. Desired interests are interdisciplinary modeling (ideally using economic production theory, more specifically Data Envelopment Analysis, system dynamics modeling/agent-based modeling, and/or Artificial Intelligence & Machine Learning) of safety critical socio-technical infrastructure systems. The candidate will also be responsible for writing project documents, preparing project presentations, assisting in the organization of workshops, writing research proposals, refereed journal and conference publications, and development of software code that complements the existing capabilities of SPL.
- PhD in Industrial and Systems Engineering and/or Operations Research or a related field. PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
- Background in interdisciplinary modeling of safety critical socio-technical infrastructure systems. Ideally using economic production theory, more specifically Data Envelopment Analysis, system dynamics modeling/agent-based modeling, and/or Artificial Intelligence & Machine Learning.
- Research in applications of socio-technical systems including issues related to use of automation, decision theory, organizational theory and/or workforce social questions.
Solid background in coding.
- Demonstrated ability to work effectively with a diverse team from multiple disciplines (systems engineering, decision theory, organizational theory, economic production theory, human factors engineering, and others).
- Demonstrated ability to mentor and lead graduate student research.
- Strong track record in publishing in high-impact peer-reviewed journals or conferences.
- Strong communication skills.
- Experience in R, Netlogo, VENSIM, Python
- Track record in securing or contributing to competitive federal grant proposals
Commensurate with experience
The successful candidate will be required to have a criminal conviction check.
About Virginia Tech
Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including the Innovation Campus in Northern Virginia; the Health Sciences and Technology Campus in Roanoke; sites in Newport News and Richmond; and numerous Extension offices and research centers. A leading global research institution, Virginia Tech conducts more than $500 million in research annually.
Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.
If you are an individual with a disability and desire an accommodation, please contact Emilee Hillman at firstname.lastname@example.org during regular business hours at least 10 business days prior to the event.
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