Lily Jampol
People Scientist & D&I Strategist at ReadySet

Paul Litvak
Product Manager at Airbnb

Wednesday, September 25, 2019

9pm–10pm EDT

Format: Online Webinar

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Description: You are curious about a non-academic career, but you don't know if it's for you. Nearly everyone who has transitioned out of academia has gone through some soul searching before taking the plunge, so you are not alone. In the first session of series on non-academic careers, Dr. Lily Jampol (People Scientist & D&I Strategist at ReadySet) will discuss with Dr. Paul Litvak (Product Manager at Airbnb) about how they made the decision to start a new journey. They will touch on several precursors to making the decision, including:

• How do we even know what it is we want?
• How sure do you have to be to make the decision to leave academia?
• What factors to think about when evaluating career paths
• How to get information on specific jobs and career paths

Please join us with questions or concerns as there will be an opportunity to discuss them live or submit your questions in advance here.

About the Presenters: Dr. Lily Jampol is a People Scientist & Consultant with the Diversity & Inclusion firm, ReadySet. Lily got her PhD in Social Psychology from Cornell, after which she did a post-doc at London Business School. She then became a tenure-track professor at Queen Mary, University of London before accepting a position at a startup in Silicon Valley in 2017. Since then, she has been working with organizations to create equitable workplaces for their communities.

Paul Litvak made the leap into industry after completing a PhD in Behavioral Decision Making at Carnegie Mellon University in 2011. He first worked as a data analyst at Facebook, working on fraud and risk management. In 2012 he went to Google where he worked as a quantitative user experience researcher analyzing student behavior via new classroom technologies. He then joined Airbnb in 2015 as a product manager, leading search ranking, and later pricing modeling.

Intended Audience: All

Prerequisite Knowledge required: None, though having started a PhD would be helpful.

Outcomes: At the end of this presentation, participants will be able to:

1. Structure evidence-gathering about your own work-needs and goals
2. Identify and challenge the factors (e.g., risk & uncertainty) that contribute to ambivalence about making a career shift
3. More effectively learn about and evaluate alternate careers

Leslie Zorwick
(email)
Hendrix College

Alicia Nordstrom
(email)
Misericordia University

Carrie Langner
(email)
California State Polytechnic University

Camille Johnson (moderator)
San Jose State University

Tuesday, July 30, 2019

2pm–3:15pm EDT

Format: Online Webinar

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Description:
Because we all go to graduate school at PhD granting institutions, we may be less familiar with the working of non-PhD granting institutions and how to successfully apply to jobs at such institutions. While a record of research productivity remains important, other aspects of application packages are equally important – including diversity statements, teaching portfolios, and how research is talked about. Three panelists from institutions at teaching-focused institutions (i.e. small liberal arts and master's granting) will talk about how to convey your interests, skills, and expertise through a well-crafted cover letter, CV, research statement, diversity and inclusion statement, and teaching statement. They'll also describe the recruiting process and what they look for in candidates.

About the Presenters: Leslie Zorwick earned her PhD at the Ohio State University. She is department chair and a Professor of Psychology at Hendrix College in Arkansas, where she runs a research group for undergraduates and studies identity and prejudice reduction.

Alicia Nordstrom earned her M.S. from Purdue University and her Ph.D. from the Pennsylvania State University. She is department chair and Professor of Psychology at Misericordia University.

Carrie Langner earned her PhD at UC Berkeley. She is Professor of Psychology at CalPoly San Luis Obispo, she studies social and health psychology.

Intended Audience: Student, Early Career, Academic Occupation

Prerequisite Knowledge required: None

Outcomes: At the end of this presentation, participants will be able to:

1. Create cover letters that address the major concerns of recruitment committees at teaching-focused institutions
2. Evaluate whether a position at a teaching-focused institution would be a good fit for them.
3. Describe the search and interview process at a teaching-focused institution.

Alexander Etz
(email)
University of California, Irvine

Julia Haaf
(email)
University of Amsterdam

Johnny van Doorn
(email)
University of Amsterdam

Friday, June 21, 2019

10am–11:30am EDT

Format: Online Webinar

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Description:
This webinar will provide attendees with a friendly, gentle introduction to Bayesian statistics, as well as demonstrate how to perform Bayesian analyses using JASP statistical software. Attendees will come away understanding the "why" and "how" of Bayesian estimation and hypothesis testing. This workshop is relevant to any student or researcher who wishes to draw conclusions from empirical data. No background in Bayesian statistics is required.

About the Presenters: Alexander Etz is a PhD student in the Cognitive Sciences department at the University of California, Irvine. His research is all over the place at the moment, but the common thread running through it all is the theory and application of Bayesian inference. Alexander recently completed his MSc. in statistics at UC Irvine, and he has taught a number of tutorial workshops on Bayesian analysis for the social sciences.

Julia Haaf is a postdoc at the Psychological Methods Unit of the University of Amsterdam. Her main research focus is on ordinal constraints in Bayesian hierarchical models. Using these constraints she investigates individual differences in cognitive tasks, and variability in meta-analysis. Julia taught research methods for undergraduates using JASP. She is currently contributing to a new JASP module for Bayesian metaanalysis.

Johnny van Doorn is a PhD candidate at the Psychological Methods Unit of the University of Amsterdam. His research focuses on the development of Bayesian analyses for ordinal data, such as rank correlations and nonparametric t-tests. He is part of the JASP programming team, and is (ironically) responsible for maintaining and improving the frequentist analyses. In addition, he teaches various workshops on Bayesian inference, cognitive modeling, and JASP.

Intended Audience: Student, Early Career, Mid-Career, Late Career, Academic Occupation, Non-Academic Occupation

Prerequisite Knowledge required: Basic knowledge of statistical tests (e.g., correlations and t-tests)

Outcomes: At the end of this presentation, participants will be able to:

1. Understand the basic theory behind Bayesian inference.
2. Conduct your own Bayesian analyses in JASP.
3. Interpret the output and report the results.

David A. Richards

Tuesday, May 21, 2019

6pm - 7pm EDT

Format: Online Webinar

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Description:
This conversational webinar will lead attendees through the process of turning a curriculum vitae into a résumé suitable for seeking employment outside academia. Discussion topics will include the differences between a CV and résumé and the process of developing the former into the latter. Practical, specific tips will be provided throughout.

The intended audience for this webinar is current graduate students, as well as recent graduate students who are early in their career since earning a graduate degree, but it may be of interest to any trained academic interested in pursuing a career outside the ivory tower.

The webinar will have a workshop component, during which we will try to present feedback specific to your situation, including on your CV and/or résumé. Before the webinar, attendees should respond to the survey at the below URL. This will help the presenter tailor the webinar to your needs.

Michael Frank
(email)
Stanford University

December 5, 2018
Format: Online Webinar

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Description:
R Markdown is a simple but very powerful way to mix R data analysis code and text. R Markdown documents are a great way to document your data analysis and create reproducible reports (e.g., that automatically render your graphs and tables and even your results section from your data). You can even use R Markdown to write your entire paper, avoiding copy-and-pasting your analyses, which can be a major source of errors in papers. The rendered documents look spiffy on the web and in print. In this workshop, we introduce R Markdown and show how it can be used as part of a reproducible writing workflow.