Postdoctoral Researcher, Econometrics and Machine Learning Department of Economics,
Prof. Matthew Harding, Deep Data Lab
JEL Classification: C – Mathematical and Quantitative Methods
The postdoctoral researcher will work closely with Professor Matthew Harding on developing and implementing projects at the intersection of machine learning and econometrics. Some of the areas of interest are recent advances in deep learning and neural networks, causal inference, high-dimensional statistical modeling, and tensor methods. The position will provide an opportunity to publish collaborative research on Big Data methods using large proprietary panel datasets, such as massive transaction-level purchase data. The postdoctoral researcher will also have the opportunity to interact with faculty in Economics, Machine Learning and Computer Science.
We are particularly interested in individuals able to demonstrate excellence in either of the following two areas:
- Mathematical statistics and theoretical econometrics by developing novel proof techniques related to areas of interest at the intersection of machine learning and more traditional approaches. The candidate is expected to show a relatively broad range of strong mathematical skills and not be limited to one particular set of models or techniques.
- Machine learning and algorithmic design with a focus on Big Data methods. The candidate
is expected to have outstanding computational skills, proven fluency in more than
one programming language (e.g. Python, R, Matlab) and familiarity with new libraries
(e.g. TensorFlow). Candidates with a strong background in Bayesian modeling are also
welcome to apply.
Salary and benefits
This position is full-time and includes benefits. Salary is commensurate with experience.
The successful candidate must possess a Ph.D. (by the start of the appointment) in Economics, Statistics, Machine Learning, Computer Science or related disciplines. More experienced candidates with a PhD completed over the past 5 years are also considered. The position is anticipated to begin in mid 2017 for one year with reappointment possible contingent upon satisfactory performance and productivity.
The University of California, Irvine is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.
Interested candidates should submit the required application materials listed below at: https://recruit.ap.uci.edu/apply/JPF03772
All candidates are required to submit:
- A cover letter with a clear statement of research interests
- Curriculum Vitae
- A job market paper
- Candidates applying for the computational track are also required to submit a GitHub repository with a relevant well-commented code sample and related documentation.
- Statement of Contributions to Diversity - Statement addressing how past and/or potential contributions to diversity will advance UCI's Commitment to Inclusive Excellence.
- Three letters of recommendation
We will conduct Skype interviews with the top candidates.