Assistant, Associate, or Full Professor (Ladder Rank): Artificial Intelligence & Public Policy

Qualifications

• Faculty candidates should demonstrate interest and contributions in both: (1) an aspect of data science vital to the design or implementation of public policy, including machine learning, artificial intelligence, natural language processing, network analysis, data privacy and security, or algorithmic fairness; and (2) a policy domain of long-term priority, including public health, public infrastructure (e.g., transportation, housing, smart cities), movement and settlement of peoples (e.g., migration, refugees, border issues), fairness and discrimination (e.g., in employment, housing, or criminal justice), international trade and finance, climate and energy policy, or defense and security policy
• Expertise in both a public policy domain and a technical domain; this is not a joint appointment, practical data science skills are necessary;
• A demonstrable history of novel technical innovation as well as the ability to point to translation and social impact from their work
• Senior applicants may have concrete examples, while junior applicants may need to describe the aspirational impact their emerging work will have;
• Experience teaching across computational/numerical and public policy-related domains;
• Ability to engage with students and colleagues with substantially different training, including classical schools of thoughts and novel approaches within fields like economics;
• Demonstrated capacity (or, for junior applicants, clear plans) to build and lead cross-sector collaborations that connect academia with government, industry, and communities, as in to shape evidence-based, AI-enabled policy
• All candidates are expected to establish a rigorous program of high-quality, sustainably-funded research that focuses on innovations in the targeted search areas

Responsibilities

• The successful applicant(s) will be expected to teach at both the graduate and undergraduate levels in support of the Data Science major/minor degree and other programs offered by the Institute

Full Description

The University of California, San Diego invites applications for one or more ladder rank faculty appointments based in the Halıcıoğlu Data Science Institute (HDSI), the academic unit of the newly formed School of Computing, Information and Data Sciences.

This is an open rank search (Assistant, Associate or full Professor) for outstanding researchers to fill our need in the field of Artificial Intelligence and Public Policy.

Economics, Political Science, Sociology, and Public Policy are all seeing rapid advancement in the ability to understand human behavior in new ways through the use of Artificial Intelligence (AI).

We seek faculty applicants who are experts in AI, data science, economics, political science, public policy, or a closely related discipline.

Faculty candidates should demonstrate interest and contributions in both: (1) an aspect of data science vital to the design or implementation of public policy, including machine learning, artificial intelligence, natural language processing, network analysis, data privacy and security, or algorithmic fairness; and (2) a policy domain of long-term priority, including public health, public infrastructure (e.g., transportation, housing, smart cities), movement and settlement of peoples (e.g., migration, refugees, border issues), fairness and discrimination (e.g., in employment, housing, or criminal justice), international trade and finance, climate and energy policy, or defense and security policy.

A focus on intersecting fields is encouraged, as in societal computing, innovations in community based participatory research using digital technologies, and human-in-the-loop decision support systems.

This search has the following priorities:

• Expertise in both a public policy domain and a technical domain; this is not a joint appointment, practical data science skills are necessary;

• A demonstrable history of novel technical innovation as well as the ability to point to translation and social impact from their work.

Senior applicants may have concrete examples, while junior applicants may need to describe the aspirational impact their emerging work will have;

• Experience teaching across computational/numerical and public policy-related domains;

• Ability to engage with students and colleagues with substantially different training, including classical schools of thoughts and novel approaches within fields like economics;

• Demonstrated capacity (or, for junior applicants, clear plans) to build and lead cross-sector collaborations that connect academia with government, industry, and communities, as in to shape evidence-based, AI-enabled policy.

All candidates are expected to establish a rigorous program of high-quality, sustainably-funded research that focuses on innovations in the targeted search areas.

This position involves teaching university students.

The successful applicant(s) will be expected to teach at both the graduate and undergraduate levels in support of the Data Science major/minor degree and other programs offered by the Institute.

Appointment will be tenured or tenure-track.

The level of appointment for the successful candidate(s) will be based on the candidate’s background and experience. The following link to the full description of the Ladder Rank Professor series is provided for your review: http://www.ucop.edu/academic-personnel-programs/_files/apm/apm-220.pdf