College of IST Privacy/Security in LLM-Driven Agentic Systems PhD Internship w/ Dr. Sharma
College of IST Privacy/Security in LLM-Driven Agentic Systems PhD Internship w/ Dr. Sharma
Employer Active
Job Alert
You will be updated with latest job alerts via email
Share
Job Alert
You will be updated with latest job alerts via email
Not Disclosed
Salary Not Disclosed
1 Vacancy
Job Description
APPLICATION INSTRUCTIONS:
CURRENT PENN STATE EMPLOYEE (faculty staff technical service or student) please login to Workday to complete the internal application process. Please do not apply here apply internally through Workday.
CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State please login to Workday to complete the student application process. Please do not apply here apply internally through Workday.
If you are NOT a current employee or student please click Apply and complete the application process for external applicants.
Approval of remote and hybrid work is not guaranteed regardless of work additional information on remote work at Penn State seeNotice to Out of State Applicants.
JOB DESCRIPTION AND POSITION REQUIREMENTS
The College/Unit of IST is seeking applicants for part-time job of Privacy/Security in LLM-Driven Agentic Systems PhD Internship w/ Dr. Sharma
About the Project:
Governance Privacy and Security Lab is conducting research at the intersection of security privacy and AI systems design.The goal of this project is to create a structured analysis of information flow in modular LLM-driven agentic systems. The focus is on identifying security privacy and control failures that emerge when autonomous modules interact across loosely enforced system boundaries. We also would like to estimate the value of privacy and security in the agentic systems from users perspective.
Internship Role:
We are seeking a highly motivated PhD intern(part-time research role) to support the development of tools models and taxonomies that expose and mitigate vulnerabilities in LLM-driven agentic systems. You will work closely with team to:
- Analyze modular architectures for unanticipated information flow
- Formalize information flow motifs and their associated threat vectors
- Assist in developing a layered threat model aligned with NIST Cybersecurity Framework principles
- Apply causal tracing influence tracking and behavioral audit techniques to real-world agentic systems
- Contribute to an academic paper and open-source tools
Qualifications:
- Enrolled in a PhD program in Computer Science Information Science Cybersecurity or related fields
- Research experience in one or more of the following: LLMs multi-agent systems privacy/ security
- Analytical and writing skills
- Experience with LLM agent frameworks or security auditing tools is a plus
Apply:
Please apply to the position to be considered. Please upload a CV and a sample publication or writing sample. Applications are reviewed on a rolling basis.
Compensation:
The starting rate for this job is $18 20 hours/week.
BACKGROUND CHECKS/CLEARANCES
Employment with the University will require successful completion of background check(s) in accordance with University policies.CAMPUS SECURITY CRIME STATISTICS
Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988 Penn State publishes a combined Annual Security and Annual Fire Safety Report (ASR). The ASR includes crime statistics and institutional policies concerning campus security such as those concerning alcohol and drug use crime prevention the reporting of crimes sexual assault and other matters. The ASR is available for review here.
EEO IS THE LAW
Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race color religion age sex sexual orientation gender identity national origin disability or protected veteran status. If you are unable to use our online application process due to an impairment or disability please contact .
Required Experience:
Intern
Employment Type
Part-Time
