Assistant Researcher

The Assistant Researcher is expected to make significant and creative contributions to research projects, applying advanced disciplinary knowledge, technical competency, and a high degree of independence. Serving as a specialized research collaborator and independent investigator, the Assistant Researcher will lead primary research and manuscript preparation. The researcher will be a key participant in the OASIS (Online and AI Systems' Integrity & Safety) Lab and work with various Communication faculty members, including Professors Hosseinmardi, Lamberson, and Kernell. Their specialized research focus will involve network science, statistical inference, and causal inference on networks, as well as the analysis and modeling of complex systems and social networks using advanced methodological frameworks.

The position requires the application of high-level technical skills derived from advanced doctoral training and research experience. The Assistant Researcher will utilize expertise in probabilistic graphical models, causal inference techniques, statistical physics, information theory, machine learning, signal processing, and optimization to address complex communication and social science research problems. They will specifically apply advanced methods for data analysis and modeling, such as community detection and link prediction. Beyond direct research, the incumbent will assist in the mentorship and training of graduate and undergraduate student researchers involved in these various departmental projects.

Professional activity and the dissemination of research are core requirements for this series. The Assistant Researcher will be responsible for preparing and submitting research findings to prestigious, peer-reviewed journals and presenting findings at national and international conferences. They will maintain active engagement in the scientific community by serving as a peer reviewer for journals such as PNAS, Science Advances, and Physical Review Letters. Additionally, the Assistant Researcher will support the department's research infrastructure by assisting the Principal Investigator and other faculty in the preparation and submission of grant proposals to secure extramural funding.

The posted UC salary scales (https://www.ucop.edu/academic-personnel-programs/compensation/index.html) set the minimum pay determined by rank and step at appointment. See Table 13A. The annual salary range for this position is $94,700 - $123,900.

Department: https://comm.ucla.edu

Applicants with a Ph.D.

Ph.D. in Computer Science, Data Science, Communication, or a closely related quantitative field at the time of application.

A strong record of professional activity, such as serving as a peer reviewer for prestigious scientific journals.

Experience leading research projects related to AI systems.

Specialized experience in network science, statistical inference on networks, and the analysis of complex systems using advanced methodological frameworks.

• 3-5 required (contact information only)

Please submit the names and contact information of three references who could be contacted at a later date regarding your application. When contacted, references are reached via email.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected status under state or federal law.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.

• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, discrimination, dishonesty, or unethical conduct, as defined by the employer.
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  UC Sexual Violence and Sexual Harassment Policy
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  UC Anti-Discrimination Policy for Employees, Students and Third Parties
• APM - 035: Affirmative Action and Nondiscrimination in Employment