Assistant/Associate Professor in Financial Technology
New Jersey Institute of Technology
Newark, NJ
Job posting number: #7111051
Posted: September 19, 2022
Application Deadline: Open Until Filled
Job Description
Position Summary:The Martin Tuchman School of Management at New Jersey Institute of Technology invites applications for a tenure-track Assistant/Associate faculty position in Financial Technology starting Fall 2023 Academic Year. Candidates must have earned their doctoral degree in finance, computational finance, applied machine learning, data mining, or statistical learning or related field in computer science with emphasis on financial technologies preferably from an accredited school. Successful candidates must demonstrate a record of scholarly accomplishment and a commitment to contributing original research into leading peer-reviewed publications. In addition, the applicant should be interested in teaching the full array of financial technology and related courses at the undergraduate and graduate levels. The individual must have completed the Ph.D. at time of appointment in September 2023 (ABD candidates will be considered).
Essential Functions:
- The main duties of the position include teaching, research and service/outreach.
- The candidate must demonstrate a record of scholarly accomplishment and a commitment to contributing original research into leading peer-reviewed publications.
- The faculty is also expected to actively engage in various Program, School, and Institute committees and participate in community service. Excellent interpersonal, communication and management skills are also required.
Prerequisite Qualifications:
- Candidates must have earned their doctoral degree in finance, computational finance, applied machine learning, data mining, or statistical learning or related field in computer science with emphasis on financial technologies preferably from an accredited school.
- We also consider applicants who are Ph.D. researchers at FinTech companies wishing to join academia.
- Desirable areas of expertise and specific research and teaching interests may include: Computational finance, Finance-related research that utilizes artificial intelligence, machine learning, block chain technology, and quantitative finance approaches, Data-Driven Financial Modeling, Financial Data Analytics.
- At the university's discretion, the education and experience prerequisites may be exempted where the candidate can demonstrate to the satisfaction of the university, an equivalent combination of education and experience specifically preparing the candidate for success in the position.
Preferred Qualifications:
- Experience in teaching courses in financial technologies.
- Professional experience in applied and theoretical financial technologies.