Job Description SummaryOrganization's Summary Statement:
The Applied Research Laboratory for Intelligence & Security (ARLIS) at the University of Maryland is a University-Affiliated Research Center (UARC) dedicated to advancing research, innovation, and technology transition to improve decision making for U.S. national security. ARLIS combines deep scientific expertise with operational insight to address challenges in intelligence analysis, cybersecurity, artificial intelligence / machine learning, quantum science, and human-machine teaming. Researchers, scientists, engineers, and analysts at ARLIS collaborate with government agencies, industry partners, and academic institutions to deliver actionable insights and transformative solutions through research and development. Employees at ARLIS work on projects of critical importance, contribute directly to the nation’s security, and are supported by a culture that values integrity, collaboration, and professional growth.
The Quantitative Methods Research Scientist will support ARLIS’s expanding research portfolio in operational innovation and information. The role will contribute to a portfolio of government-sponsored projects addressing emerging challenges in areas such as artificial intelligence/machine learning (AI/ML), decision support, information warfare, language assessment and training, natural language processing (NLP), and open-source intelligence (OSINT). The role may include a focus on research development, prototyping, experimentation, systems integration, and/or field deployment. Final appointment title and responsibilities will be based on qualifications and matched to programmatic needs.
Must be able to obtain a US security clearance. If selected, must meet the requirements for access to classified information and will be subject to a government security clearance investigation that includes criminal and credit history checks, as well as verification of U.S. citizenship, birth, education, employment, and military history. Final offer is contingent upon the candidate’s ability to successfully obtain the necessary interim Secret security clearance, as determined by the government sponsor, prior to commencing employment.
Minimum Qualifications:
Education:
● Doctoral degree or Master’s and 5 years of research experience in a relevant field, from an accredited college or university.
Experience:
● Evidence of sound scholarly production (e.g., conference presentations, published journal articles, published code, published datasets, technical reports).
● Demonstrate all the relevant skills required for carrying out quantitative social science research.
● Background in and demonstrated proficiency with quantitative social science research methods and statistical analyses.
● Experience leading basic and/or applied research projects.
Knowledge, Skills, and Abilities:
● Extensive experience with one or more statistical analysis programs (e.g., Matlab, R).
● Skill in research design.
● Familiarity with social science concepts.
● Skill in the use of Microsoft Office products.
● Ability to multi-task and prioritize assignments.
● Ability to analyze situations and determine the best recourse for response.
Physical Demands:
Sedentary work performed in a normal office environment; exerts up to 10 pounds of force occasionally and/or negligible amount of force frequently or constantly to lift, carry, push, pull or otherwise move objects, including the human body. Ability to attend meetings both on and off campus. Spending long hours in front of a computer screen.
Licenses/Certifications: N/A
Preferred Qualifications:
Education:
● Doctoral degree or Master’s with 5 years experience in psychology, neuroscience, political science, linguistics, data analytics, computer science, or related field.
Experience:
● Comfort working both independently and collaboratively in a fast-paced, evolving environment.
● Strong organizational skills and attention to detail.
● Active, or eligible for a security clearance; prior clearance at SECRET or higher that is active or inactive is preferred; current TS/SCI clearance strongly preferred.
● Foreign language capabilities, at the advanced level.
● Programming skills (e.g., Python, C++).
● Experience working with multidisciplinary project teams.
● Experience working on federal contracts or grants.
● Experience with Artificial Intelligence/Machine Learning research.
● Experience with population modeling.
● Experience with human subjects research design.
Additional Job DetailsRequired Application Materials: Cover Letter, Resume, List of References
Best Consideration Date: 10/10/26
Posting Close Date: N/A
Open Until Filled: Yes
Financial Disclosure RequiredNo
DepartmentVPR-Applied Research Lab for Intelligence & Security
Worker Sub-Type Faculty Regular
Salary Range$120,000 - $180,000
For more information on Regular Faculty benefits, select this link.
Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify anyone from employment. Before any adverse decision, the finalist will have an opportunity to provide information to the University regarding disclosable background check information. The University reserves the right to rescind the offer of employment or otherwise decline or terminate employment if the information reported by the background check is deemed incompatible with the position, regardless of when the background check is completed.
Employment EligibilityThe successful candidate must complete employment eligibility verification (on Form I-9) by presenting documents that establish identity and work authorization within the timeframe required by federal immigration law, and where applicable, to demonstrate renewed employment authorization. Failure to complete employment eligibility verification or reverification within the timeframe set forth by law may result in suspension or termination of employment.
EEO StatementThe University of Maryland, College Park is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment. Please read the University’s Equal Employment Opportunity Statement of Policy.
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