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Postdoctoral Researcher, Econometrics and Machine Learning

Recruitment Period

Open August 23rd, 2018 through November 15th, 2018
If you apply to this recruitment by November 15th, 2018, you will have until November 21st, 2018 to complete your application.

Description

Postdoctoral Researcher, Econometrics and Machine Learning
Department of Economics, UC Irvine
Prof. Matthew Harding, Deep Data Lab
JEL Classification: C – Mathematical and Quantitative Methods

Job Description

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 nonparametric modeling. The position will provide an opportunity to publish collaborative research on Big Data methods using large proprietary panel datasets, such as transaction data, credit data or financial data. The postdoctoral researcher will also have the opportunity to interact with faculty in Economics, Machine Learning and Computer Science.

Fields

We are particularly interested in individuals able to demonstrate excellence in either of the following two areas:
a) Machine learning and algorithmic design with a focus on Big Data methods. The candidate is expected to have outstanding computational skills, have experience in handling large datasets, and have proven fluency in statistical programming (e.g. Python, R) and current tools (e.g. TensorFlow, Pytorch). Candidates are expected to have strong empirical econometrics skills (e.g. panel data, forecasting, program evaluation, quantile models, non-linear and discrete choice models).

b) 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. The statistical analysis of neural networks is of particular interest.

Salary and benefits:

This position is full-time and includes benefits. Salary is commensurate with experience.

Qualifications:

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 2019 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.

Application procedure:

Interested candidates should submit the required application materials listed below at: https://recruit.ap.uci.edu/apply/JPF04918

Application materials:

All candidates are required to submit
a) A cover letter with a clear statement of research interests
b) Curriculum Vitae
c) A representative academic paper using machine learning
d) Candidates applying for the empirical/computational track are also required to submit a GitHub repository with a relevant well-commented code sample and related documentation.
e) Statement of Contributions to Diversity - Statement addressing how past and/or potential contributions to diversity will advance UCI's Commitment to Inclusive Excellence.
f) Three letters of recommendation

We will conduct Skype interviews with the top candidates. Additional interviews may be conducted at the AEA Winter Meeting in Atlanta.

Job location

Irvine, CA

Requirements

Document requirements
  • Cover Letter - A cover letter with a clear statement of research interests

  • Curriculum Vitae - Your most recently updated C.V.

  • Representative Academic Paper Using Machine Learning

  • GitHub Repository - Required for candidates applying for the empirical/computational track. GitHub repository with a relevant well-commented code sample and related documentation.

    (Optional)

  • Statement of Contributions to Diversity - Statement addressing how past and/or potential contributions to diversity will advance UCI's Commitment to Inclusive Excellence.

  • Misc / Additional (Optional)

Reference requirements
  • 3 letters of reference required

How to apply

  1. Create an ApplicantID
  2. Provide required information and documents
  3. If any, provide required reference information
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