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            Bullard Research Fellows

            Multiple iSchool post-doctoral research positions in Austin

            The School of Information at the University of Texas at Austin invites applications for up to four new full-time post-doctoral Bullard Research Fellows research positions to start in 2020, with the exact start date depending on applicant availability and completion of doctoral studies. The salary for successful candidates will be $54,000 per year, plus a standard package of benefits. These are 12-month positions that can be renewed for a second year contingent upon performance.

            We are seeking applicants with active research plans in any of the following areas:

            BRF1. Archives and Memory Institutions

            Areas of particular interest include digital curation, archives, record keeping, archival infrastructures and systems, computer history, and cultural heritage informatics. Faculty in this area able to serve as mentors include Ciaran Trace and Patricia Galloway. 5% of this Bullard post-doctoral fellow’s time will be devoted to working with the Professor Fred Mason Bullard archives at the Jackson School of Geosciences and the Briscoe Center for American History.

            BRF2. Search as Learning

            We are seeking applicants with active research plans in the areas of searching as learning, understanding searching as a human learning process, assessing learning in the search process, designing search systems to support various forms of human learning, evaluation of learning-centric search systems, supporting creativity in search, search user interfaces, information searching behavior, and interactive information retrieval. This position will be mentored by Soo Young Rieh.

            BRF3. Impacts of Emerging Technologies and Social Informatics

            A portion of the successful candidate’s time will be spent working on projects related to blockchain technologies in multiple sectors including healthcare and the arts. This position will be mentored by Eric T. Meyer.

            BRF4. Neuro-Information Science / NeuroIR

            There is now a growing interest in the use of neuro-physiological NP methods in human‐information interaction (HII) and interactive information retrieval (IIR) research. Data obtained from NP methods are complementing more traditional data sources. They offer potential for the creation of new information search models and robust predictive models that will enable the development of neuro‐adaptive IIR systems. This position will provide an opportunity for a post-doc to shape this emerging research area. The successful candidate will focus on using neuro-physiological evidence (e.g., from eye-tracking, EEG) to deepen understanding of HII and lay foundations for neuro‐adaptive IIR systems. Experimental studies will be conducted in our state-of-the-art Information eXperience (IX) lab. Preferred educational background / experience includes some of the following: cognitive/experimental psychology, cognitive neuroscience, human-computer interaction, machine learning, neuroergonomics, and interactive information retrieval. This position will be mentored by Jacek Gwidzka.

            BRF5. Designing Fair Al and Algorithms

            AI systems trained and evaluated on data may not only reproduce data bias but even amplify it. Unfortunately, even defining data bias is difficult, let alone detecting and mitigating it. It is difficult to detect and eliminate bias from data, as it can creep in through various insidious ways, and determining the best algorithmic criterion of fairness is very challenging and has been largely devoid of human input. To remedy this, we are investigating human-centered bias detection, measurement, evaluation, and feedback to complement existing algorithmic approaches. We are interested in candidates from varying disciplines, including information and computer science, philosophy, design, psychology, sociology, and science and technology studies. The ideal candidate would appreciate and be familiar with diverse views of fairness: algorithmic, societal, philosophical, etc. This Postdoctoral Fellow will be primarily mentored by Amelia Acker, Andrew Dillon, Ken Fleischmann, Min Kyung Lee, and Matthew Lease. The Fellow will also be invited to engage with us in Good Systems, a UT Grand Challenge to design AI technologies that benefit society.

            BRF6. Designing Human-Centered AI to Fight Misinformation

            Misinformation and disinformation threaten societal ability to find and recognize reliable information online, with inaccurate information risking harm across governmental, personal, and commercial spheres (e.g., voting, health care decisions, and financial markets). Automated AI models may help with fact-checking, but when many people distrust even well-known news outlets and fact-checking services, how can an AI model explain its outputs to people and earn human trust? How can we design human-centered AI models and interfaces that effectively amplify human abilities? The ideal candidate would bring an appreciation and familiarity with both HCI and AI. This Postdoctoral Fellow will be primarily mentored by Amelia Acker, Andrew Dillon, Jacek Gwidzka, and Matthew Lease. The fellow will also be invited to engage with us in Good Systems, a UT Grand Challenge to design AI technologies that benefit society.

            BRF7. Datasets and Machine Learning / AI

            Datasets drive Machine Learning, but who is behind the wheel? Data is fueling AI progress in machine learning, yet the design, science, and engineering of these datasets remains largely underdeveloped. We know little today about the work of dataset creation and how alternative dataset design practices impact progress in the AI field. To accelerate AI progress and minimize risk of harm (e.g., biased datasets yielding biased models), we are qualitatively studying the ecosystem of how today’s AI datasets are proposed, funded, designed, created, and used. The ideal candidate will be comfortable with both qualitative and quantitative methods and have familiarity with machine learning from data. This Postdoctoral Fellow will be primarily mentored by James Howison and Matthew Lease. The Fellow will also be invited to engage with us in Good Systems, a UT Grand Challenge to design AI technologies that benefit society.

            BRF8. AI in Health

            AI is going to fundamentally change our healthcare systems. How might it enhance the current clinical decision support systems by adding data-driven design to improve the efficiency and reduce the physician burnout becomes one of the most important problems in healthcare. In this project, the candidate will work with teams from School of Information and Dell Medical School to develop simple, transparent, and fair data analytical methods to summarize the clinical practices of similar cohorts and present them in a way that are not offensive to doctors and effortless to grasp. This data-driven design will be applied in medical imaging diagnosis, migraine risk calculation, and evidence-based medicine. This Fellow will be mentored by Ying Ding.

            BRF9. Innovation and Collaboration

            Innovation starts from collaboration. But finding the right collaborators at the right time can be hard. In this project, the candidate will work with Ying Ding and her team to analyze collaboration patterns from 29 million PubMed articles which author name disambiguation, bio-entity extraction, and funding information have been processed and integrated. Interesting collaboration patterns from creative teams in the medical domain and their evolutions along the time, space, and funding support will be important findings to understand the relationship between innovation and collaboration.

            BRF10. Transitions to Peer Production in Grant-Funded Scientific Software Projects

            How can research grant-funded software projects transition to sustained open source/peer production collaboration? What can projects do during their grant periods to make this transition more likely? We are seeking a postdoc to join our project studying an NSF funded set of projects. In particular the postdoc would drive an interview-based study, enhancing our existing content analysis derived dataset. Ideal for an emerging scholar interested in the organization of work in science, online collaboration, collective intelligence, and software collaboration. Required: experience interviewing people about their work and analyzing those interviews. Desirable: ability to process CSV (or RDF) datasets using R tidyverse; experience with fuzzy sets or QCA analyses. The postdoc would be mentored by James Howison.

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            These post-doctoral positions do not include any obligation to teach; however, successful applicants who wish to enhance their teaching record will be able to teach up to one course annually as part of their normal workload; this may be done either as a co-lecturer with a faculty member, or as an independent lecturer. All post-docs will be given opportunities for guest lecturing and will be expected to give public seminars.

            Each post-doctoral fellow will have access to up to $5,000 annually for research expenses and travel to professional conferences and research opportunities. A laptop computer will also be provided for the duration of the fellowship.

            For all of the above positions, we only seek candidates with excellent research and leadership abilities and a commitment to contributing to the UT Austin iSchool and the field of information more broadly while accelerating their career.

            Qualifications

            On the start date of the position, candidates must hold a doctoral degree. That degree must be in a field relevant to their area of research and will normally have been awarded no more than three years prior to their start date. Exceptions to the three year limit will be considered on a case-by-case basis, particularly for candidates who have taken positions outside academia and wish to return to academic research. Candidates must articulate clearly in their application materials what independent project they propose to work on during their fellowship in addition to their time working on iSchool faculty projects.

            About the University of Texas iSchool

            The UT Austin iSchool is a premier research and education leader in the field of information, changing the future by engaging the present and preserving the past. The iSchool is committed to making a difference in the lives of all people by enabling and supporting the organization and experience of information in ways that make the world a better and fairer place. We are changing how people interact with information and technology, and the ways that we protect and preserve our collective memories. At the iSchool we are discovering new and vital knowledge about information, educating the next generation of leaders in the information professions, developing new scholars who will advance knowledge, improving society through service and collaboration, and applying human-centered values to all of our work.?

            The UT Austin iSchool is a founding member of the international iSchools caucus, and has a long history of interdisciplinary scholarship and research focused on the human, social, cultural, and technical aspects of information. Our program is consistently ranked among the top programs in information internationally. We are a stand-alone school with strong connections across the university and with other institutions nationally and internationally; we are particularly interested in applicants who will further strengthen and extend our collaborative network. We offer master’s and doctoral degree programs, dual master’s degree programs with various disciplines, an integrated bachelor’s in computer science/master’s in information studies, and an undergraduate minor. Our Master of Science degree in Identity Management and Security is offered jointly with the UT Center for Identity. For more details on our current degree offerings, see our Courses page.

            UT Austin is one of the world’s leading research universities, with an internationally distinguished faculty. UT Austin embraces interdisciplinary research, and is the home to more the 200 dedicated research units and centers. For more information on UT Austin, see our About UT Austin page.

            About Austin

            Austin is a city bursting with entrepreneurial spirit, a commitment to personal freedom, and a passion for discovery. 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. It is a city with natural beauty in abundance, with a glittering lake that runs through the center of the city, year-round sunshine, and a location in the picturesque Hill Country of central Texas. Austin is a creative center that attracts the best and the brightest from around the world. 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), which includes Film, Music, and Interactive Festivals. Austin serves as the corporate headquarters for Fortune 500 companies such as Dell, Whole Foods, and ABM Industries, plus successful tech start-ups such as Aspyr, Hoover’s, and RetailMeNot. Austin also hosts research and development offices for major technology-oriented companies such as Amazon, AMD, Apple, Cisco, eBay, Facebook, Freescale, Google, IBM, Indeed.com, Intel, Oracle, Samsung, and Texas Instruments, who have established major operations in Austin to draw from the highly skilled talent the university produces. Savills World Research ranks Austin #1 in the Savills Tech Cities Index. U.S. News and World Report rated Austin #1 in its Best Places to Live list for the last 3 consecutive years. Expedia ranks Austin #1 in its 21 super cool US cities list. More information on Austin can be found on our About Austin page.

            Application Instructions

            Applications will be accepted until each available position is filled. We will begin to review applications and interview candidates starting on May 1st, 2020.

            These post-doctoral positions are for academics in the early stages of their career who demonstrate exceptional potential as a scholar and researcher. Applicants should either have completed a doctoral degree, or be able to convincingly demonstrate that they will complete the degree before they intend to start this post-doctoral fellowship (e.g. by documenting a scheduled viva/final defense). Required materials:

            1. Current CV
            2. Cover letter, approximately 2-4 pages (1,000 – 2,000 words). Required elements of your cover letter include:
              • which position you are applying for (e.g. BRF1 or BRF9)
              • when you would be available to start your fellowship
              • a clear articulation of your fit with the UT Austin iSchool, addressing how your expertise overlaps with, enhances, or expands upon the research area indicated for your position of interest. Please include names of mentors that you would like to work with.
              • a research statement that includes a description of the focus of your planned independent research and publications during the fellowship, what sort of resources would you need to do that work, and an explanation of how the research builds on and goes beyond work you have already done.
            3. Writing sample (1), preferably a pre- or post-print of a first-authored publication
            4. References (4), including names and contact details (we may contact your references at any stage in the hiring process unless candidate requests otherwise).

            Questions about these positions can be sent to postdocs@ischool.utexas.edu.

            Please apply via Interfolio's Faculty Search solution. If you do not have a Dossier account with Interfolio, you will be prompted to create a free account prior to applying for the position.

            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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