Postdoctoral Fellow, Knowledge, Generative AI, and Power

Job Posting Title:

Postdoctoral Fellow, Knowledge, Generative AI, and Power

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Hiring Department:

School of Journalism and Media

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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:

Immediately

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Position Duration:

Expected to Continue Until Sep 01, 2024

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Location:

UT MAIN CAMPUS

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Job Details:

General Notes

This position has an expected start date of September 1st, 2024. Earlier start date can be negotiated.

Deadline

Review of applications will begin on March 1, and will continue until the position is filled.

About

About Good Systems: Good Systems is a University of Texas at Austin research grand challenge that seeks to design AI technologies alongside broader policy and decision-making systems that can protect and improve our world. Our interdisciplinary campus-wide research effort brings together humanists, social scientists, and technologists to investigate how to define, evaluate, and build ethical AI systems that will transform society for the better.

About UT Austin: UT Austin ranks among the 40 best universities in the world, and is a leading research university, attracting more than $650 million annually for discovery. UT Austin embraces interdisciplinary research and is home to more than 200 dedicated research units, centers, and research grand challenges, including Good Systems. 

About Austin : Austin has a vibrant, internationally renowned music, film, and art scene, along with a thriving economy that leads the way in the technology, engineering, and health care sectors. Often referred to as the “Live Music Capital of the World,” Austin hosts major annual events such as the Austin City Limits Music Festival and South by Southwest (SXSW). Austin serves as the home for corporate headquarters and research and development centers for many Fortune 500 companies and new startups, providing opportunities for collaboration and student placements for internships and careers. 

Purpose

Good Systems , Ethical AI at UT Austin, is recruiting a postdoctoral fellow to conduct research on the theme of Knowledge, Generative AI, and Power as it relates to Good Systems core research projects, which investigate the ethical implications of AI technologies in society in the areas of surveillance and privacy, racial equity, smart cities, mis- and dis-information, human-robot interaction, and smart hand tools and the future of work. The postdoctoral fellow will report to Dr. Dhiraj Murthy, but the research will be interdisciplinary. For more information on research themes and participating faculty, please view the Good Systems core research projects .

Possible research directions may include but are not limited to the following:

• Misinformation and disinformation

• Social media and influence and role of generative AI in information integrity

• AI, Health and Social Media

• Inequality, race, and social stratification

• Impact of technological systems on knowledge creation

• Impact of knowledge creation on technological systems

• Data governance and regulation

Candidates should explain their interest in one or more of these directions in their application.

Responsibilities

• Become familiar with the six Good Systems core research projects by meeting with team leadership, attending team meetings, and reading project scholarly outputs.

• Develop, collect, and refine ideas for cross-project research opportunities on the theme Knowledge, Generative AI, and Power , and collaborate with relevant core project researchers to explore and develop a cross-cutting research topic. 

• Lead writing of manuscript(s) related to Knowledge, Generative AI, and Power , submit to conferences and/or journals, and present and disseminate findings.  

• Lead, develop, and submit external funding proposals.

• Other duties as assigned.

Required Qualifications

• Applicants must hold or receive a Ph.D. in a relevant field before the start of the appointment. Ph.D. must have been received within the last three years.

• Ability to lead collaborative research projects.

• Strong writing skills demonstrated by first-authored peer-reviewed journal papers or peer-reviewed conference proceedings papers.

Preferred Qualifications

• Experience communicating social science ideas to interdisciplinary technical audiences (such as computer scientists, engineers, and humanists).

• A general understanding of computational methods (e.g. machine learning, network analysis, natural language processing or formal statistics) sufficient for constructive dialogue with practitioners.

• Research focus connected to Knowledge, Generative AI, and Power and ethical AI, broadly defined.

• Educational backgrounds that are interdisciplinary or that span multiple disciplines, ideally ranging across the socio-technical spectrum.

• An interest in broader societal dimensions of AI, including social, policy, and regulatory aspects.

Salary Range

$75,000

Working Conditions

• May work around standard office conditions and in laboratories

• Repetitive use of keyboard at a workstation

• Hybrid work schedule options

Required Materials

• Resume/CV

• 3 work references with their contact information; at least one reference should be from a supervisor

• Letter of interest

• Research Statement (proposed project that you would be interested in pursuing, 2-3 pages)

Inquiries

Please direct any general questions about the position to Lea Sabatini, Good Systems Program Director ([email protected] ).

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.