Postdoctoral positions in data science and statistics, are available under the joint supervision of Dr. Edoardo Airoldi and Dr. Kenichiro McAlinn.

We are seeking outstanding postdoctoral candidates with a strong interdisciplinary background across statistics, machine learning, finance, and economics. Potential projects include: (A) modelling and analysis of high-frequency financial data; (B) developing models for high-dimensional time-series data; (C) methods to improve information flow for sequential decision making; (D) modelling high-dimensional, dynamic financial networks; (E) causal inference and design of experiments in dynamic systems (i.e., leveraging reinforcement learning and bandits); (F) causal inference with strategic agents (i.e., leveraging game theory and strategic network formation models). The ideal project develops a new quantitative approach and applies it to an important problem. Areas of special interest include financial and economic data; dynamic models, latent factor models, network models, ensemble methods, causal inference, design of experiments, sequential decision making.

This joint research effort offers a highly energetic environment for working on a wide range of challenging methodological problems in data science, statistics, and beyond. We are involved in a collaboration with Wells Fargo. Postdocs will collaborate on these projects. We also work closely with collaborators at other universities and in industry, in order to identify and address technical problems for which a solution would have a substantial impact in the world. Postdocs will contribute to projects at the Fox Data Science Center, housed in the Fox School of Business at Temple University.
Salary and benefits are competitive and commensurate with experience. Review of applications will begin immediately and continue until positions are filled.

The ideal candidates will have deep knowledge of statistics and machine learning, and a strong track record of research in quantitative methods, with interests toward applications in economics and finance, evidenced by high quality publications; be able to communicate and collaborate with student/postdocs and external PIs; and be able to carry out research and develop ideas inde-pendently. Programming skills (e.g., R, Python, Matlab) are also required. Candidates whose doc-toral dissertation focused on time series, high-dimensional statistics, causal inference, and network science are encouraged to apply.

HOW TO APPLY. Applications should include: (a) cover letter; (b) full curriculum vitae; (c) brief research statement; (d) evidence of excellence in research; (e) the names and contact info of three references. Please send all materials to: Dr. Kenichiro McAlinn at and Dr. Edoardo M. Airoldi at Please note that we only review electronic submissions.

Temple University is an Equal Opportunity/Affirmative Action Employer and specifically invites and encourages applications from women and minorities.