Virginia Tech
Job Description
Applications are invited for a National Science Foundation funded (LEAP HI Program #2051685) Postdoctoral Associate position with the System Performance Laboratory (SPL) (www.splvt.com) in the
Grado Department of Industrial and Systems Engineering
at 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 year if mutually desired), totaling up to a maximum of 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 modelling (ideally using economic production theory, more specifically Data Envelopment Analysis, system dynamics modelling/agent‑based modelling, and/or Artificial Intelligence & Machine Learning not excluding other modelling frameworks) of safety‑critical socio‑technical infrastructure systems. The candidate will be primarily responsible for writing and submitting refereed journal and conference publications, research proposals, preparing project documents and project presentations, assisting in the organization of a workshop, working with large datasets, and developing software code that complements the existing capabilities of SPL. As part of the position duties the candidate will be expected to travel to Belgium to visit engineers and managers at INFRABEL (National Belgian Railway Company).
Required Qualifications
Ph.D. in Industrial and Systems Engineering and/or Operations Research or a related field (e.g., human system integration, human‑machine interaction, computer science); Ph.D. must be awarded no more than four years prior to appointment with a minimum of one year eligibility remaining.
Background in interdisciplinary modelling of socio‑technical systems.
Research in applications of socio‑technical systems including issues preferably related but not limited to automation, decision theory, organizational theory and/or workforce social questions.
Experience in data science and working with large datasets.
Demonstrated ability to work effectively with a diverse team from multiple disciplines (e.g., systems engineering, decision theory, organizational theory, economic production theory, human factors engineering, and others).
Demonstrated ability to mentor and lead graduate student research.
Previous experience in publishing in high‑impact peer‑reviewed journals or conferences.
Strong communication skills.
Preferred Qualifications
Familiar with economic production theory, more specifically Data Envelopment Analysis, experience with system dynamics modelling/agent‑based modelling, and/or Artificial Intelligence & Machine Learning not excluding other theoretical or modelling frameworks.
Experience in R and Python, and/or NetLogo, and/or VENSIM.
Track record in securing or contributing to competitive federal grant proposals.
Additional Details Exempt: Not eligible for overtime. Employment type: Restricted. Salary: Commensurate with experience. Hours per week: 40. Review date: 12/01/2025. Initial duration: 12 months effective January 2026. The successful candidate will be required to have a criminal conviction check.
Equal Opportunity Statement 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, ethnicity or 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. Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. If you are an individual with a disability and desire an accommodation, please contact
David Price
at
dprice30@vt.edu
during regular business hours at least 10 business days prior to the event.
#J-18808-Ljbffr
Grado Department of Industrial and Systems Engineering
at 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 year if mutually desired), totaling up to a maximum of 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 modelling (ideally using economic production theory, more specifically Data Envelopment Analysis, system dynamics modelling/agent‑based modelling, and/or Artificial Intelligence & Machine Learning not excluding other modelling frameworks) of safety‑critical socio‑technical infrastructure systems. The candidate will be primarily responsible for writing and submitting refereed journal and conference publications, research proposals, preparing project documents and project presentations, assisting in the organization of a workshop, working with large datasets, and developing software code that complements the existing capabilities of SPL. As part of the position duties the candidate will be expected to travel to Belgium to visit engineers and managers at INFRABEL (National Belgian Railway Company).
Required Qualifications
Ph.D. in Industrial and Systems Engineering and/or Operations Research or a related field (e.g., human system integration, human‑machine interaction, computer science); Ph.D. must be awarded no more than four years prior to appointment with a minimum of one year eligibility remaining.
Background in interdisciplinary modelling of socio‑technical systems.
Research in applications of socio‑technical systems including issues preferably related but not limited to automation, decision theory, organizational theory and/or workforce social questions.
Experience in data science and working with large datasets.
Demonstrated ability to work effectively with a diverse team from multiple disciplines (e.g., systems engineering, decision theory, organizational theory, economic production theory, human factors engineering, and others).
Demonstrated ability to mentor and lead graduate student research.
Previous experience in publishing in high‑impact peer‑reviewed journals or conferences.
Strong communication skills.
Preferred Qualifications
Familiar with economic production theory, more specifically Data Envelopment Analysis, experience with system dynamics modelling/agent‑based modelling, and/or Artificial Intelligence & Machine Learning not excluding other theoretical or modelling frameworks.
Experience in R and Python, and/or NetLogo, and/or VENSIM.
Track record in securing or contributing to competitive federal grant proposals.
Additional Details Exempt: Not eligible for overtime. Employment type: Restricted. Salary: Commensurate with experience. Hours per week: 40. Review date: 12/01/2025. Initial duration: 12 months effective January 2026. The successful candidate will be required to have a criminal conviction check.
Equal Opportunity Statement 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, ethnicity or 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. Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. If you are an individual with a disability and desire an accommodation, please contact
David Price
at
dprice30@vt.edu
during regular business hours at least 10 business days prior to the event.
#J-18808-Ljbffr