Instructional Faculty in Psychological Data Science
University of Texas Austin Department of Psychology College of Liberal Arts
United States

Description

The Department of Psychology at The University of Texas at Austin seeks a candidate for an Assistant or Associate Professor of Instruction to teach undergraduate and possibly post-graduate courses. Professional faculty positions are 3-year renewable contracts and salary will be dependent upon position and qualifications. Background check conducted on applicant selected.

Qualifications

The successful candidate will be responsible for teaching introductory statistics with an emphasis on practical approaches to visualizing and analyzing real data. When covering traditional parametric tests, p-values should be treated as continuous probabilities (rather than as significant/not significant), and other sources of information, such as effect sizes and prior knowledge, should be emphasized. The general approach taken should be broadly consistent with the editorial Moving to a World Beyond “p < 0.05" in The American Statistician (2019).

Required proficiencies:

a) PhD in Psychology or other related social and natural science fields

b) Expertise in modern research methods and analytics used in the social and behavioral sciences

c) Proficiency with R/RStudio

Candidates may also demonstrate expertise in one or more of these preferred proficiencies:

a) Mixed effects modeling

b) Bayesian statistics

c) Structural equation modeling

d) Machine learning (e.g. random forests, elastic net, ect)

e) Text mining and web scrapping, wrangling large publicly available datasets

f) Expertise in Python, or other programing languages for data science

g) Familiarity with open source and open science approaches to the behavioral sciences, including method to insure reproducibility of analysis

Application Instructions

Interested applicants should submit a letter of interest, a current curriculum vita, and three letters of reference.


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