University of Colorado, Boulder, Department of Information Science Application Deadline: December 15, 2023. The Department of Information Science in the College of Media, Communication and Information seeks an outstanding candidate for a tenure-track Assistant Professor starting in Fall 2024, with a special focus on applicants who conduct research in accessibility and design.

National Taiwan University, Department of Library and Information Science Application Deadline: January 10, 2024. The Department of Library and Information Science at National Taiwan University is seeking to employ two full-time faculty. 1. Qualification: *Doctoral degree in library and information science, information management, information and communication, educational technology and related fields *Those who can teach required courses in LIS are preferred 2. Documents Required: *Photocopy of doctoral diploma; Those who have not yet received the diploma at the time of application must provide a formal statement from the degree-granting institution indicating that it will be in hand by the time of appointment *Transcripts of the master’s and doctoral studies *Photocopy of working experience certification *Resume *List of publications and the full text of the representative and supporting works (must include print copy in the application package; must also send the electronic files to lis@ntu.edu.tw ) The applicant should designate his/her representative and supporting works and provide the full text of the works for the hiring review. The representative work should include at least two published journal articles/book chapters or one scholarly monograph. The doctoral dissertation may serve as the applicant’s representative work if assistant professor is the intended rank. If the appointment begins on August 1, 2024, the representative works should be published no earlier than August 2019, and the supporting works should be published no earlier than August 2017. If the appointment begins on February 1, 2025, the representative works should be published no earlier than February 2020, and the supporting works should be published no earlier than February 2018. 【For the definition of representative works please refer to: https://edu.law.moe.gov.tw/EngLawList.aspx?id=FL008629】 * Course plans and syllabi (must include course introduction, teaching goals, weekly schedules for 16 weeks, and required readings). 3. Other Requirements: *The applicants who pass preliminary review by our search committee will be invited to give a presentation to our faculty (travel expenses to be paid by the applicant) *All applications will not be returned. 4. Date of appointment and position official rank: The appointment begins on August 1, 2024, or February 1, 2025. The official rank appointed is according to working experience and qualifications. 5. Application deadline: January 10, 2024 6. How to apply: *All the documents must be prepared in printed format and mailed to the Department of Library and Information Science Address: Professor Yu-Wei Chang Department of Library and Information Science, National Taiwan University No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan, R. O. C. *The applicants who are abroad can email the electronic package. If the applicant is recommended by the search committee as a candidate for external review, the department staff will notify and will have to receive the complete hard copy of the application. Email: lis@ntu.edu.tw Tel: 886-2-3366-2958 Fax: 886-2-2363-2859

University of Wisconsin-Madison, Information School Application Deadline: December 15, 2023. The University of Wisconsin-Madison's Information School seeks highly qualified candidates for up to two tenured positions in information sciences. These faculty positions will be academic nine-month, tenure-track appointments at the Associate Professor level, to start August 2024. Applications at the Professor level may be considered in exceptional cases.

Indiana University, Luddy School of Informatics, Computing and Engineering at IU Indianapolis Application Deadline: January 02, 2024. The Department of Human-Centered Computing at Indiana University’s Luddy School of Informatics, Computing, and Engineering at Indianapolis invites applicants for a Tenure-Track faculty position in Extended Reality (XR). Exceptional researchers are being sought to join our fast-growing department. Candidates must demonstrate an outstanding scholarly record of research, exhibited by high-impact peer-reviewed publications and a forward-looking, vigorous research agenda that will secure competitive, external funding. The ideal candidate will strengthen and complement faculty research in the department by using creative and innovative approaches to address fundamental HCI and informatics challenges with broader societal impact. Candidates will leverage the strengths of the IUI campus, including its well-connected urban campus, civically engaged faculty, and interdisciplinary environments connected to nationwide leadership in the health and life sciences. Indianapolis and the surrounding region has seen significant recent investment through public-private partnerships that bring opportunities for innovation to the Hoosier state. Within the last year, key partnerships in edge computing, industry 4.0, and chip manufacturing have created opportunities for the Luddy School to maximize its impact and research agendas in innovation within Indiana’s robust health, manufacturing, and sports ecosystems.

Indiana University, Luddy School of Informatics, Computing and Engineering at IU Indianapolis Application Deadline: January 02, 2024. The Indiana University Luddy School of Informatics, Computing and Engineering at IU Indianapolis invites applications for open rank tenured or tenure-track assistant, associate or full professor positions in the discipline of various computer science areas. Appointments will begin August 1, 2024 on the Indianapolis campus. Candidates must demonstrate an outstanding scholarly record of teaching and research, exhibited by high-impact peer-reviewed publications and a forward-looking, externally funded research agenda as Principal Investigator (PI). Research expertise in any promising area of computer science will be considered with an emphasis on Artificial Intelligence, Machine Learning, Data Science, and their applications in biomedical and health sciences.

University of California Los Angeles, The Department of Information Studies Application Deadline: November 26, 2023. The Department of Information Studies at UCLA is seeking to fill an Assistant Professor position with an anticipated start date of July 1, 2024, with expertise in using critical methods to improve opportunity and equity for Latinx communities. Strong candidates will have a deep understanding of research in their field and expertise bridging critical theories and methods to address Latinx communities as creators, subjects, and users of information and data. UCLA aims to achieve federal designation as a Hispanic Serving Institution by 2025. This search is conducted in partnership between the Chicano Studies Research Center and the School of Education and Information Studies. Faculty hired through this search are expected to maintain an active affiliation to the CSRC and encourage the success of Latinx and first-generation scholars. We welcome candidates whose professional experience and personal background have facilitated their ability to better serve students from Latinx, low-income, and other traditionally underrepresented communities. Candidates should further demonstrate the ability to teach and mentor doctoral students, masters, and undergraduates in an engaging and accessible manner. Faculty are expected to have an inclusive approach to mentoring and advising, and experience working with diverse student identities (e.g. gender, race, sexual orientation, income, immigration status).

University of Washington, Information School Application Deadline: November 30, 2023. The University of Washington Information School invites applications for a 12-month appointment as a Postdoctoral Scholar to work on a project titled “Developing a Spanish-language Homosaurus: Using Multi-language Linked Data to Enhance LGBTQ Resource Discoverability,” which was recently funded by the National Endowment for the Humanities. The anticipated start date is July 1, 2024. The fellowship may be completed residence in Seattle at the iSchool or as fully or partially remote depending on the preferences of the selected fellow.

Gary Marchionini, University of North Carolina at Chapel Hill It is always hard to predict the long-term impact of any newly hyped technical development — to estimate which innovation is just part of the caravan of hype cycles and which will endure long-tail impact growth after the cycle peaks. In 2023, it is hard to attend a meeting or experience media without encountering Generative AI (GenAI) as the revolutionary technology that will change everything. For baby boomers, this is the third iteration of ‘AI will change the world’ and so there is some skepticism about whether we are indeed in another technical revolution or simply another incremental information technology iteration. My estimation is that the confluence of carefully layered deterministic and probabilistic algorithms running on networks of very high-performance processors that have access to enormous volumes of structured and unstructured inputs is going to be ‘capital S’ significant — another step in humankind amplifying and augmenting physical and mental existence. GenAI is less about one specific technical advance (e.g., machine learning or neural nets, or large language models-LLMs) but rather the natural and inexorable advance of our species’ ability to use tools and knowledge to amplify and augment human capabilities and activities. We are experiencing the latest turn in Douglas Engelbart’s observation more than 60 years ago about electronic tools augmenting the intellect. The ‘generative’ modifier for AI speaks to new capabilities that output novel products (e.g., text or images) and parallel the advances in systems that produce designed products and outcomes (e.g., additive 3D printing, self-assembling molecules, autonomous robots and weapons, synthetic biology spawns). Big changes bring excitement and fear. There are examples of GenAI applications that advance science, health, and education — each day brings new augmentations of human endeavor such as support for protein engineering or on-the-fly clinical decision-making during radiation treatment. Likewise, each day brings examples of consequential errors (so called ‘hallucinations’) or tragic effects (e.g., autonomous vehicle accidents). Additionally, there are serious overarching concerns about the impact of GenAI on work, entertainment, politics, personal identity, global economy, military power, social well-being, and human dignity. The excitement and fear bring enormous investments in resources and human talent, breathless debates, and increasing attention and action from government agencies.[1] Given this context for GenAI and related technologies, what are the roles and responsibilities for information and library science professionals? Why ILS Professionals? The responsibilities discussed here apply to information professionals in corporate, government, or other kinds of settings, however, I use the term ‘information and library science professional’ rather than the more general ‘information professional’ here because so many of these responsibilities flow from the historical values and practices of librarians, archivists, and information theorists. All information professionals in any setting will assume these roles and responsibilities within their specific work context. Information and Library Science (ILS) professionals have skills, perspectives, and practices that are essential to human interests in the AI-augmented world. We are especially crucial because of our human-centered approach to information and technology impact. For ILS professionals, human interest is not an add-on or afterthought but rather the reason we do the work at all — -it is fundamentally baked into information generation, management, and use. We are clearly positioned to approach an AI-augmented world from a human-centered perspective (Shneiderman, 2022). ILS professionals are concerned with information integrity and trust so that humanity can advance with confidence, justice, and equality. ILS professionals have long traditions of managing large-scaled information streams and repositories. ILS professionals have been active participants in pioneering information retrieval research and evaluation since the post-WWII era that gave rise to search engines, LLMs, and recommender systems. ILS professionals take a fundamentally human-centric approach to the needs of patrons, clients, and the public. ILS professionals have been active partners in advancing human-centered design and evaluation research and practice. ILS professionals have long accepted responsibility for managing institutions and services devoted to preserving the products of human memory and activity, and defending these institutions and services as public goods. ILS professionals are committed to a culture of sharing and equitable access — librarians, archivists, and curators operate cooperative loans (e.g., interlibrary loan) and distributed digital libraries. What are the critical roles of ILS professionals in an AI-augmented world? Certainly, ILS professionals will learn to leverage AI augmentations to better serve their clients, organizations, and humanity’s information needs. However, given the developments and challenges that the latest wave of technology bring, together with the skills, critical perspectives, and cultures of ILS, there are several key responsibilities that ILS professionals must accept to ensure that humanity progresses with dignity and equanimity. Six types of responsibility follow that are categorized into inputs, use, outputs, evaluation, education, and reflection[2]. 1. INPUTS. Training set selection and validation (collection development policy, workflow and data genesis documentation). o Librarians, archivists, and curators create collection development policies that align patron communities with extant and new information products and knowledge representations. These policies determine how acquisition resources are invested and thus generate scrutiny and debate, and therefore demand careful specification and justification. ILS professionals are well-suited to consider the quality and appropriateness of materials for different stakeholders and communities. The selection of training sets for large language models and other generative algorithms is crucial and although early models use large samples of convenience (e.g., harvests of swaths of the public WWW), more specialized and vetted selection and validation policies will surely be needed. ILS professionals have important roles to play in validation, curation, and selection of training data. To do so, we must build upon traditional collection development strategies to make the structure and provenance of data sets transparent or at least documentable. Just as importantly, we must work to develop understanding of the nuances of different algorithms so that training sets may be well-suited to the problem domains to which the generative tools are applied.[3] 2. USE. Prompt construction and refinement. o Sometimes called prompt engineering, one of the current challenges of GenAI systems entails translating human needs and desires into signals that a complex black box computational model can understand. Information professionals help people articulate their information needs. Librarians learn how to conduct reference interviews that help people explicate their information needs and clarify and refine their queries through conversation and iterative consideration of preliminary results. As interactive information retrieval systems researchers and designers, ILS professionals investigate ways to incorporate relevance feedback in system processes and guide how people reformulate queries with an eye toward how interactive query formulation and revision improve search efficiency and effectiveness[4]. Not only are ILS professionals well-prepared to adapt these skills to help people develop and hone prompts but we can leverage our experience to create systematic investigations of how generative models change as millions of people interact with them over time. This requires focus on the interaction of human iterations with base models that were trained on extant data. In essence we can study how human interaction affects how generative systems learn and evolve over time. 3. OUTPUTS. Model and output documentation, workflows, disclosure, declaration, and citation. o Librarians, records managers, data stewards, and knowledge managers have deep expertise in collecting, classifying, and preserving physical and digital resources. Our expertise in meeting the challenges of curating and managing digital libraries of dynamic assets such as active code repositories or social media streams will be essential to adding metadata to training sets and workflows as well as context to outputs, recommendations, and decisions in an AI-augmented world. ILS professionals have been leaders in developing standards and procedures for collecting and preserving research data and working with publishers to formalize conflict of interest statements and other disclosures. This expertise will be crucial to ensuring that AI-augmentation is documented and consequently trusted. Whether the aim is to build upon existing knowledge to create new knowledge or to protect intellectual property, ILS professionals have crucial roles to play in documenting the workflows and context of GenAI and other technologies. Documentation for all types of human endeavor is essential to scientific, legal, economic, and historical progress. Scholarship and human progress depend on understanding the genesis, flow, and application of ideas. Public and private libraries, archives, databases, and repositories are essential to research and innovation, and sophisticated patent and copyright regimes have evolved to reward novel applications of knowledge. Twenty-first century technologies and techniques demand expanded and extended documentation efforts to continue human progress[5]. GenAI outputs that are used for decision making or to drive manufacturing or to manage large-scale systems are difficult to document due to complexity (e.g., the number of parameters), opaqueness (e.g., ‘hidden’ layers of reinforcement learning), and economic control (e.g., proprietary processes). It is especially important that ILS professionals engage in documenting workflows, design decisions, inputs, outputs, applications, and other contextual factors so that trust, additional progress, and history are served by these technologies. 4. EVALUATION. AI system development and evaluation that amends traditional models and metrics with new models and metrics appropriate to interactive generation of content, objects, and organisms. o For more than 30 years, the ILS community has collaborated with the computer science and computational linguistic communities to formalize evaluation competitions for retrieval systems. These collaborations laid the foundations for model and system assessments, including the creation of metrics beyond traditional recall/precision.[6] ILS professionals were active in expanding evaluation metrics beyond system performance to human performance variables and concerns (e.g., satisfaction, engagement, fatigue, learning). GenAI will require new use cases, test tasks, and outcome metrics. Already, some groups have initiated this work and ILS professionals must join in to ensure that authentic task environments and human interaction metrics are included, and that specifications use consistent vocabularies for evaluations and publication[7]. 5. EDUCATION. Inspire, educate, and foster critical understanding and access to stored and generated information products and streams. o ILS professionals have long been champions of open access to information and proponents of literacy. Electronic information environments bring new challenges to free expression and new media for human expression. AI-augmentation will surely accelerate challenges to free speech, trust, and evidence of expertise and authority. We must shun becoming the authority stamp for ‘truth’ but rather strive to provide clearly delineated imprimaturs for information products and guides or tools for people to us in making their own determinations about what is disinformation or misinformation or credible information. ILS professionals’ experience in advocating for and providing training for literacy to all, our incorporation of new media in public collections, our opposition to censorship, our expertise in critical assessment of knowledge assets, and our devotion to equal access have prepared us to take leadership roles as new products and outcomes of GenAI applications affect individuals and society. We have important responsibilities to be active participants in policy discussions and regulatory actions. To carry out these responsibilities we must learn and work to understand both the applications and limitations of GenAI and design clear educational programming appropriate to diverse populations of learners[8]. In addition to being advocates for responsible and human-centric applications of GenAI, we are also responsible for ensuring that people understand the importance of materiality to human existence. ILS professionals have long experience managing and preserving the physical artifacts of human creativity and endeavor. We understand why physical materials have inherent value that cannot be digitized or computed — that knowledge artifacts have sensual characteristics (feel, smell, damage) that carry meaning. We understand that people are and understand that they are embodied in temporal and physical spaces. It is our responsibility to ensure that fully intelligent and actualized people appreciate and differentiate this materiality as well as the outputs of the artificial. 6. REFLECT. Promote and advocate for equitable individual and social access to powerful AI augmentation tools and products. o ILS professionals are inherently interdisciplinary bridge builders. We work across different scholarly and practitioner communities and have developed trust from both privileged and underserved populations. It is imperative that we use this expertise and perspective to ensure that an AI-augmented world serves all people rather than only those with power and privilege. Just as we have created shared libraries of resources and tools for our constituents, open access collections of GenAI tools and services are needed. Additionally, just as we advocate for open access to ideas and information resources today, we must advocate for open AI systems, policies, and practices to serve the public good. We cannot know today whether in 15 years everyone on our planet will have customizable and personalized AI augmentations immediately at hand on their phones, watches, or implants[9], or whether these augmentations will be limited to government or large corporate entities. What we do know is that there are enormous new opportunities and challenges in an AI-augmented world. Be prepared to be awed and disappointed — be realistic. ILS professionals are prepared to play crucial roles in ensuring that all of humanity prospers and benefits. However, this is not automatic, it will require courage and energy to accept the responsibilities and challenges the coming decades will bring. We are up to the challenge. Bender, E., Gebru, T., McMillan-Major, A. & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? FAccT 21. ACM ISBN 978–1–4503–8309–7/21/03, https://doi.org/10.1145/3442188.3445922. Sayash Kapoor and Arvind Narayanan substack book AI Snake Oil. https://www.aisnakeoil.com/ Shneiderman, B. (2022). Human-Centered AI. Oxford U. Press. See also, Google Group human-centered-ai@googlegroups.com; on behalf of; Ben Shneiderman ben.shneiderman@gmail.com U.S. Senate Judiciary Committee Subcommittee on Privacy, Technology and the Law hosted a hearing titled “Oversight of A.I.: Rules for Artificial Intelligence.” https://techpolicy.press/transcript-senate-judiciary-subcommittee-hearing-on-oversight-of-ai/ European Union AI Act https://artificialintelligenceact.eu/the-act/ Liang, P. et.al, (2023). Holistic Evaluation of Language Models. Transactions on Machine Learning Research October 2023. https://arxiv.org/pdf/2211.09110.pdf. See also Center for Research on Foundation Models. https://crfm.stanford.edu/helm/latest/ Watson, J.L., Juergens, D., Bennett, N.R. et al. De novo design of protein structure and function with RFdiffusion. Nature 620, 1089–1100 (2023). https://doi.org/10.1038/s41586-023-06415-8 [1] Examples include: California’s 2019 BOT Disclosure Law requires BOTs to disclose that they are automated processes rather than human actors. The far-reaching European Union AI Act of 2021 aims to ensure that “AI should be a tool for people and be a force for good in society with the ultimate aim of increasing human well-being.” Numerous U.S. hearings and meetings have been held with a variety of laws and regulations proposed or making their way through legislation (e.g., U.S. Senate Judiciary Committee Subcommittee on Privacy, Technology and the Law hosted a hearing titled “Oversight of A.I.: Rules for Artificial Intelligence.” https://techpolicy.press/transcript-senate-judiciary-subcommittee-hearing-on-oversight-of-ai/) [2] This list is not meant to be exhaustive but represents key challenges today. One overarching responsibility not made explicit is for us to continue to learn and discover new ways to serve humanity’s information needs. [3] For example, diffusion models are used to identify promising new proteins by leveraging the structures in curated protein databases, reducing the number of lab trials by orders of magnitude (Watson et.al, 2023). This amplification of manual trial and error procedures is possible because biochemists and information specialists have carefully curated protein databases over decades. This is not the case for many other kinds of generative problems without carefully curated databases. ILS professionals are well-prepared to work with disciplinary experts to first tell the difference between what kinds of approach will work for different data conditions, and second, to help in the creation of curated data that lends itself to specific AI amplifications or augmentations. [4] Perhaps ILS professionals would want to map classical search strategies such as successive fractions, building block, and citation pearl growing to emerging prompting strategies such as least-to-most, tree-of-thought, chain of thought, and majority vote. [5] Other documentation challenges include managing records of manufacturing and supply chain events in complex, global production (e.g., Apple’s micro etching of quick codes on iPhone screens starting at glass sheet production and including assembly operations executed on other continents); managing records of 3D printed objects and organisms (e.g., StanfordBASE Lab’s additive printing of layers of cells to generate a human heart); and documentation systems for the inevitable development of bit-level metadata. [6] The Text Retrieval Evaluation Conference has had ongoing evaluations for more than 30 years expanding from early text retrieval evaluations to multimedia, cross-language, question answering, social media search, and other topics (https://trec.nist.gov/). [7] Liang et al., have created an ambitious framework for evaluating LLMs, including sample cases that illustrate approaches for 16 core scenarios (e.g., IR, sentiment analysis, summarization, question answering) using 7 metrics (accuracy, calibration, robustness, fairness, bias, toxicity, and efficiency). Liang, P. et.al, (2023). Holistic Evaluation of Language Models. Transactions on Machine Learning Research October 2023. https://arxiv.org/pdf/2211.09110.pdf. See also Center for Research on Foundation Models. https://crfm.stanford.edu/helm/latest/ [8] There is a plethora of courses, conference workshops, and papers from credible sources that explain the principles of large language models, deep learning, and other elements of GenAIs (e.g., Coursera alone offers dozens of courses, some with more than 100,000 students enrolled). There is also a host of papers, blogs, and conference workshops that critically discuss the technical limitations and practical implications of GenAI (e.g., Bender, E., Gebru, T., McMillan-Major, A. & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? FAccT 21. ACM ISBN 978–1–4503–8309–7/21/03, https://doi.org/10.1145/3442188.3445922; Sayash Kapoor and Arvind Narayanan substack book AI Snake Oil. https://www.aisnakeoil.com/. These resources are dwarfed by the relentless flow of popular press and social media stories about magical applications or apocalyptic futures and it is information professionals responsibility to work to organize and curate resources for patrons and the public. [9] We can imagine that the computational power and data resources will be cheap and ubiquitous so that anyone can easily call upon a model that draws on all public data as well as all personal data from emails, social media, and other systems to answer or guide life activities on the fly (and plug and play different proprietary or specialized data to generate ‘what if’ scenarios and outputs). I suggest that all the responsibilities discussed here continue to obtain.

University of Maryland, College Park, College of Information Studies Application Deadline: December 11, 2023. The College of Information Studies (the INFO College) at the University of Maryland has launched a search for an Assistant Professor in the area of information science concepts and methodologies to study important social science problems in the broad field of government and politics. The INFO College invites applications for a full-time, TTK Assistant Professor who is highly competent, energetic, collegial, and interested in joining our exciting, diverse, and inclusive environment. The faculty member will have a joint appointment at INFO (75%) and GVPT (25%), with a tenure home in INFO. The faculty member will be expected to teach courses in both INFO and GVPT, as well as to contribute to teaching and service to the newly formed undergraduate Major in Social Data Science, which is an INFO-BSOS joint program. We seek a candidate who will build upon our record of educating information and political scientists committed to leadership, service, research, and innovative practice and impact. In particular, candidates whose scholarship speaks to the following broad substantive topics are encouraged to apply: Social media politics Information disorder (misinformation, disinformation, etc.) Online political and civic participation Policy and governance for emerging technologies Digital democracy and data justice Data science for policy analysis Role of political institutions in production and dissemination of information Political and moral values of information systems The political economy of information systems While these areas of expertise are of particular interest, candidates with expertise and interest in other relevant topics that apply data science methods are encouraged to apply. Candidates whose work recognizes the information norms and assets of marginalized communities particularly relating to the topics above and other relevant topics, are especially encouraged to apply. To learn more about the position, the university, and to apply, please visit: https://ejobs.umd.edu/postings/114626. To learn more about the INFO College, please visit: https://ischool.umd.edu/about/ .

The University of Oklahoma, School of Library and Information Studies Application Deadline: Open until filled. The School of Library and Information Studies (SLIS) In the Dodge Family College of Arts and Sciences at the University of Oklahoma (OU) seeks an innovative scholar in the area of Knowledge Organization for an open rank, tenured/tenure track faculty position with a starting date of August 16, 2024. SLIS is expanding its strengths in Knowledge Organization through innovative research, teaching, and service. Knowledge Organization concerns the following: Indexing, Description, Representation, Classification, and Organization of information resources for users’ needs in both traditional and digital environments, using both manual and automated methods. The successful applicant for this position will join the University of Oklahoma SLIS faculty in the education of undergraduate, master’s, and doctoral students in various capacities including teaching courses, supervising independent studies, advising, and serving on students’ committees. The teaching responsibilities include two courses per semester. A successful candidate for this position will be able to teach Master of Library and Information Studies required core course LIS-5043 Organization of Information and develop new courses such as, for example, undergraduate-level Knowledge Organization related courses. The faculty member will conduct scholarly research resulting in publications in peer-reviewed journals, book chapters, edited books, books, and conference papers. Seeking opportunities for internal and external funding is also expected. Additionally, the candidate will be committed to engagement in service to the profession and in the shared governance within the university. This position is based on the Norman campus. The salary is competitive and is commensurate with qualifications and experience. The University of Oklahoma offers an excellent benefits program. For further benefits information please access the Human Resources website at https://hr.ou.edu/.

University of Arizona, School of Information Application Deadline: December 01, 2023. The School of Information at the University of Arizona invites applications for multiple tenure track Assistant or Associate Professor positions to start in Fall 2024. We are looking for candidates with expertise in all areas of artificial intelligence. Required qualifications: A Ph.D. in information science, computer science, or a related discipline. A productive and innovative research record with promising future directions. Preferred qualifications: Expertise in trustworthy artificial intelligence or bias and equity in machine learning Experience instructing, engaging, and mentoring students at the graduate and/or undergraduate level. Ability to write compelling proposals for external funding. A record of outreach to and impact on schools, local communities, businesses, or other groups not often involved in information science. Experience working collaboratively with faculty, students, and staff from different disciplines, cultures, and academic backgrounds. Equal Opportunity Employer Minorities/Women/Vets/Disabled

University of Kentucky, School of Information Science Application Deadline: Open until filled. This assistant professor position will support our program in information communication technology. Teaching/research areas could include but are not limited to information systems, system design, application development, software design, cloud computing, artificial intelligence, human computer interaction, computer security, databases, or health informatics.