Student Rsch. Intern - Data-Genomics-CR

Student Rsch. Intern

• Data-Genomics-CR#26-16918 $761.60
• $880.00/week Newport Beach, CA $0 weekly stipends $19.04
• $22.00/hour $761.6
• $880 weekly base pay All On-site 12 weeks Job Description Day Shift Our Client, a Healthcare company, is looking for a Student Rsch. Intern
• Data-Genomics-CR for their Newport Beach, CA location.

Responsibilities:

Work under faculty and research staff mentorship to design and execute a defined research project. Perform data collection, cleaning, analysis, and visualization using clinical, genomic, or translational datasets. Assist with genomic data review (e.g., sequencing results, variant interpretation, molecular profiling summaries) as applicable to the project. Conduct literature reviews and synthesize scientific findings to support research hypotheses and interpretation. Apply basic statistical and analytical methods to answer research questions. Maintain accurate documentation of methods, analyses, and results. Prepare figures, tables, and written summaries of findings. Actively participate in research meetings, project updates, and presentations. Contribute significantly to the drafting of an abstract and/or manuscript with the goal of submission to a scientific journal or conference by the end of the internship.

Requirements:

Strong interest in biomedical, clinical, translational, or genomics research. Ability to work independently with a high level of responsibility and follow projects through to completion. Strong analytical, problem-solving, and organizational skills. Excellent scientific writing and presentation skills with attention to detail. Proficiency in Microsoft Word, Excel, and PowerPoint. Ability to work collaboratively in a multidisciplinary research environment.

Preferred Skills & Experience:

Experience with literature searches, reference management, or academic writing. Prior data analysis, research methods, or laboratory/clinical research exposure. Familiarity with genomics, bioinformatics concepts, electronic medical records, or research datasets. Basic knowledge of statistics, R, Python, SPSS, or similar analytical tools (helpful but not required).