美国弗吉尼亚理工大学博士后职位招聘–工业和系统工程和/或运营研究或相关领域
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, 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 modeling (ideally using economic production theory, more specifically Data Envelopment Analysis, system dynamics modeling/agent-based modeling, and/or Artificial Intelligence & Machine Learning not excluding other modeling 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 of software code that complements the existing capabilities of SPL. As part of the position duties will be the expectation that the candidate would travel to Belgium to visit with the engineers and managers at INFRABEL (National Belgian Railway Company).
Required Qualifications
– PhD in Industrial and Systems Engineering and/or Operations Research or a related field (e.g., human system integration (human factors engineering; systems engineering and/or computer science); human-machine interaction (human factors engineering; computer science); other). 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 socio-technical systems.
– Research in applications of socio-technical systems including issues preferably related but not limited to the use of 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 modeling/agent-based modeling, and/or Artificial Intelligence & Machine Learning not excluding other theoretical or modeling frameworks.
– Experience in R and Python, and/or Netlogo, and/or VENSIM.
– Track record in securing or contributing to competitive federal grant proposals.