Research Associate - Hybrid

Description

This position will work a hybrid schedule which includes a combination of working both onsite on Campus and remote.

UCSD Department of Psychiatry is one of the most innovative and productive academic departments in the country, offering challenging career opportunities in advanced educational programs, cutting‑edge research, and state‑of‑the‑art clinical services. The department is committed to providing a dynamic learning environment and growing opportunities for its talented and dedicated employees.

Under supervision, the incumbent will support research operations and data‑analytic activities for substance‑abuse research within the Department of Psychiatry. This entry‑level position is designed to provide structured training in research data coordination, statistical analysis, and reproducible research practices in an academic research setting. The incumbent must be able to work independently or as part of a team in a fast‑paced environment with changing priorities.

Primary responsibilities include assisting with the organization, cleaning, and management of behavioral, clinical, and genetic datasets; supporting statistical and computational analyses using programs such as R and/or Python following established protocols; and contributing to longitudinal, multilevel, and genomics‑informed analytic workflows. The incumbent will assist with literature reviews, manuscript preparation, and the preparation of progress reports for funding agencies and institutional review boards.

Additional duties include supporting research operations such as documentation, scheduling, record maintenance, and coordination of internal research workflows. The incumbent will be expected to keep meticulous paper and digital records and assist with other project and miscellaneous tasks as needed.

• Theoretical knowledge in psychology or related field preferred as typically attained by a Bachelor’s degree.
• Demonstrated knowledge of basic research functions, including data collection, documentation, and adherence to research protocols.
• Basic skills in data organization and statistical analysis using established tools and scripts; familiarity with data security and confidentiality practices.
• Proven ability to assist with routine data analyses, including basic descriptive statistics and structured analytic tasks, under supervision.
• Proven ability to communicate information clearly and professionally, both verbally and in writing, with investigators and research staff.
• Strong organizational and multitasking skills, including the ability to prioritize tasks, manage competing deadlines, and maintain accuracy.
• Demonstrated experience to document analytic steps, maintain clear records, and follow established documentation standards.
• Proven ability to work both independently and as part of a team, follow guidance, and seek clarification or support when needed. Must be able to work in a fast‑paced environment with changing priorities.
• Strong interpersonal and professional communication skills, including responsiveness and attention to detail.
• Must be able to maintain confidentiality.
• Familiarity with genetic and bioinformatics concepts (e.g., GWAS, polygenic scores) and willingness to learn new analytic tools as part of the role.
• Ability to assist with genetic research workflows (e.g., quality control steps, data preparation) following established protocols and under supervision.
• Basic familiarity with command‑line or Linux‑based environments, or willingness to learn as needed for research tasks.
• Demonstrated experience following multi‑step analytic workflows using documented scripts or standard operating procedures.
• Experience working with moderately sized research datasets and basic proficiency in R and/or Python for data handling and analysis.
• Familiarity with standard computing environments and exposure to research computing systems or cloud‑based platforms.
• Proven ability to manage time effectively, complete assigned tasks on deadline, and follow version‑controlled workflows when applicable.
• Exposure to commonly used genetic analysis software (e.g., PLINK, EasyQC, LDSC, SAIGE) or willingness to learn these…