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Postdoctoral Fellow - The Computational Affective and Social Cognition Lab (CASCogLab)

University of Texas at Austin

Job Description


Job Posting Title:

Postdoctoral Fellow - The Computational Affective and Social Cognition Lab (CASCogLab)

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Hiring Department:

Department of Psychology

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Position Open To:

All Applicants

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Weekly Scheduled Hours:

40

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FLSA Status:

Exempt

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Earliest Start Date:

Feb 01, 2023

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Position Duration:

Expected to Continue Until Feb 01, 2024

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Location:

UT MAIN CAMPUS

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Job Details:

General Notes

The CASCog Lab, an interdisciplinary lab at the intersection of Psychology and Artificial Intelligence, is housed in the Department of Psychology, in the College of Liberal Arts at the University of Texas at Austin. In our lab, we are interested in studying how people understand the emotions and other mental states of others, and distilling such insights into building computers that can better understand these uniquely human states. For more information about the research conducted in the lab, please visit the lab website at https://cascoglab.psy.utexas.edu/ , or Prof. Ong's website at https://cascoglab.psy.utexas.edu/desmond .

  • One Postdoctoral Fellow will work primarily on projects related to empathic interventions. Ideal candidates will have a background and interest in: social-psychological interventions (e.g., reducing intergroup conflict; increasing empathy; changing attitudes), and/or expertise in empathy.  

  • Another Postdoctoral Fellow will work primarily on projects related to affective cognition, or understanding how people reason about others' emotions, for example in ambiguous situations, or in situations where others are deliberately displaying emotional expressions. 

There are a number of active research areas in the lab, including: how do people understand emotions from multiple modalities of information (facial expressions, voice, text, psychophysiological signals), building computational models of such emotion understanding, and doing machine learning research to build better AI models.

The Postdoctoral Research Fellow is an ideal training position to prepare the candidate for future job applications in academia (e.g., tenure track) or in industry. The position is for two years, with an option to renew subject to satisfactory performance and at the discretion of the Principal Investigator, and subject to availability of funds.

Purpose

The Postdoctoral Research Fellows will work closely with the Principal Investigator, Prof. Ong, on all stages of the research process: from conducting literature reviews, designing and running empirical studies, to data analysis and computational modelling of the data, to writing up the results for publication and presentation. The Postdoctoral Research Fellows will propose and lead research projects of their own under the supervision of the Principal Investigator. Finally, the postdoctoral research fellows will contribute to grant writing and aspects of grant management as part of their training.

Responsibilities

  • Leading research projects and handling all aspects of the research process, including:

    • Handling ethics review and compliance

    • Recruiting participants for empirical studies

    • Managing and analyzing data

    • Managing code bases

    • Supervising undergraduate research assistants

  • Writing up research into manuscripts, and presenting research at conferences.

  • Grantsmanship, including applying for training fellowships or assisting with larger grant applications.

  • Other duties as assigned.


Required Qualifications

Candidates should have a Ph.D. degree in Psychology, Cognitive Science, Computer Science, or a related field. The degree must have been conferred no more than three years prior to the start date. As this is a research position, the ideal candidate should have substantial research experience and research-relevant skills, including:

  • Conducting psychological experiments (designing and constructing experiments, recruiting and consenting participants, collecting data).

  • Statistical skills, including data analysis.

  • Programming skills in R and/or Python.

  • Self-motivated, responsible, detail-oriented, and with excellent time management skills

  • Clear communication skills and ability to work in a team

  • Positive and enthusiastic attitude towards learning.


Preferred Qualifications

  • Experience with or willingness to learn web development (HTML/Javascript/CSS)

  • Experience with or willingness to learn open science practices (e.g., version control on Github, reproducible analysis reports in RMarkdown, pre-registration)

  • Experience with or willingness to learn machine learning (e.g., PyTorch)



Salary Range

$50,000 + depending on qualifications


Working Conditions

  • Typical office environment

  • May involve occasional weekend hours


Required Materials

  • A copy of your CV

  • A Cover Letter (not more than 3 pages) stating your research interests and long-term goals. Please also discuss your prior research experience, statistical and computational skills, and how your research aligns with that of the lab.

  • The names, affiliations, and contact information of two individuals (e.g., Professors, previous employers) who will be willing to provide a recommendation letter describing your research experience and character. We will only solicit letters for shortlisted candidates.

Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section; you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded.  Once your job application has been submitted, you cannot make changes.

Important for Current university employees and contingent workers: As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs. If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left hand navigation menu and then update the sections in your Professional Profile before you apply. This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume. In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.) that were noted above.

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Employment Eligibility:

Please make sure you meet all the required qualifications and you can perform all of the essential functions with or without a reasonable accommodation.

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Retirement Plan Eligibility:

The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length. This position has the option to elect the Optional Retirement Program (ORP) instead of TRS, subject to the position being 40 hours per week and at least 135 days in length.

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Background Checks:

A criminal history background check will be required for finalist(s) under consideration for this position.

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Equal Opportunity Employer:

The University of Texas at Austin, as an equal opportunity/affirmative action employer , complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.

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Pay Transparency:

The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.

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Employment Eligibility Verification:

If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form.  You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States.  Documents need to be presented no later than the third day of employment.  Failure to do so will result in loss of employment at the university.

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E-Verify:

The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university’s company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:

  • E-Verify Poster (English) [PDF]
  • E-Verify Poster (Spanish) [PDF]
  • Right To Work Poster (English) [PDF]
  • Right To Work Poster (Spanish) [PDF]

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Compliance:

Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031 .

The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.


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