Technical Assistant - Advance Research

University of New Mexico
$18.00 Hourly
United States, New Mexico, Albuquerque
1 University Of New Mexico (Show on map)
Nov 21, 2024
Requisition IDreq31630 Working TitleTechnical Assistant - Advance Research Pay$18.00 Hourly CampusHealth Sciences Center (HSC) - Albuquerque, NM DepartmentIM Translations Informatics (852T) Employment TypeStudent Employment Student Type StatusNon-Exempt Background Check RequiredNo For Best Consideration Date12/2/2024 Position Summary Join our team at the Malec Lab in the Division of Translational Informatics at UNM Health Sciences Center! We're working on a cutting-edge project to better understand and prevent Alzheimer's Disease. This is your chance to be part of groundbreaking research that could make a real difference in people's lives. What You'll Do * Help gather, organize, and analyze data for our Alzheimer's research * Assist in data analysis using R, Python, and SQL * Support the team in literature reviews and database management * Learn about advanced research methods in medical science and data analytics * Explore the use of large language models in biomedical research * Gain exposure to epidemiological studies and causal inference techniques * Collaborate with researchers from different scientific backgrounds * Potentially contribute to scientific writing and publication processes * Assist in natural language processing tasks to extract knowledge from scientific literature * Help in building and analyzing knowledge graphs * Contribute to applying extracted knowledge to real-world patient health data analysis Why Join Us? * Gain hands-on experience in a real research lab * Learn about Alzheimer's Disease and cutting-edge research methods * Develop advanced skills in data analysis, scientific computing, and AI applications in healthcare * Explore epidemiological approaches and causal inference in medical research * Opportunity to contribute to and learn about scientific paper writing * Engage with cutting-edge NLP techniques and knowledge graph applications for analyzing healthcare data * Build your resume for grad school or future career opportunities * Flexible hours to fit your class schedule * Potential for academic credit or work-study compensation Minimum Qualifications Enrolled in a degree seeking program at UNM, Enrolled at least half-time (6 hours) at UNM for fall and spring semesters (Audit hours do not count), and if Work Study, you must meet Satisfactory Academic Progress. Preferred Qualifications Preferred Qualifications * Current undergraduate student (junior or senior preferred) * Major in Biology, Psychology, Biostatistics, Computer Science, Mathematics, or related field * Experience with R, Python, and SQL (coursework or projects) * Strong interest in medical research, especially brain health and data analysis * Attention to detail and good organizational skills * Ability to work independently and as part of a team * Interest or experience in using large language models (LLMs) is a plus * Interest or experience in epidemiology and causal inference is a plus * Interest in or experience with scientific writing is a plus * Interest in natural language processing, knowledge graph construction, and applying these to analyze patient health data is a strong plus Application Instructions Only applications submitted through the official UNMJobs site will be accepted. If you are viewing this job advertisement on a 3rd party site, please visit UNMJobs to submit an application. Cover letter explaining interest in the position and highlighting relevant skills (including experience with R, Python, SQL, any exposure to large language models, background in epidemiology or causal inference, scientific writing experience, and any experience or strong interest in NLP and knowledge graphs) Attach resume or CV Attach current class schedule or availability If available, a sample of your scientific writing or a brief description of any relevant projects in NLP or data analysis or other related areas. The University of New Mexico is committed to hiring and retaining a diverse workforce. We are an Equal Opportunity Employer, making decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability, or any other protected class.