The Deng’s team in the department of Psychiatry and Behavioral Sciences is seeking applicants for a part time research assistant (RA) available immediately.
For more information about Dr. Deng please visit:
https://profiles.stanford.edu/huiqiong-deng
For more information about the research project please visit:
https://www.clinicaltrials.gov/ct2/show/NCT04198961?term=huiqiong+deng&draw=2&rank=1

Below please find more detailed information about this position in Q&A format. If you are interested, please send an email with your CV attached. In the email please highlight, in bullet points, your time availability and flexibility in your schedule, statistical analysis skills, training history, and relevant research experience. For example:
• Can start now, available through June 2022, and can work 5-10 hr per wk with quite some flexibility in my schedule (Cannot do Th due to work/class…)
• Statistical analysis skills: proficient in SAS
• Training history: CITI
• Relevant research experience: worked as RA on EPIC chart review study in 2020 with responsibilities to retract data, clean and sort data…

In addition, please send some of your code samples in Python used to acquire data from a database and then process it in Excel format (please add notes as needed to explain function of commands briefly).

If you have a reference/support letter from your previous employer or mentor, please send along and this will be highly valued.

For any questions and/or formal application, please send an email to hdeng397@stanford.edu and cc our research coordinator at kai.y.huang@outlook.com with this in the email subject line by F, 4/16 5pm: “FirstNameInitialLastName_Degree_estimated graduation yr” e.g. JDoe_BScandidate_2022. Our team will reach out to the potential candidates for brief Zoom interview soon. Thank you very much. Early response is appreciated, and the position will be filled on first serve first come basis if we have multiple qualified applicants.

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What are the requirements for this position?
-- You are required to have a Stanford SUNET ID. The candidate should be familiar with Python. The job is mainly but may not limited to acquire data from a database and then process it in Excel format. The RA is expected to write code to crawl the links, download the data, clean up the data (removing null entries, etc) and reorganize and filter the data (based on factors e.g. medication doses and days) to make it ready for data analysis.
Statistical analysis skills are not required but highly valued. Based on the research design, we will have two groups and multiple time points. And we will use repeated measurement random effect module for continuous variables and use Chi square testing for proportional data.
Before starting to work on this project, the RA is required to take Collaborative Institutional Training Initiative (CITI) training (takes a few hours), etc. You’ll be paid for the hours you need to complete all required trainings. You are expected to complete the training ASAP so you can start to work soon. Please highlight any biomed especially medical chart research experience and/or with CITI training, which is viewed as a plus.
All the work can be done remotely as long as you have internet access.

How many hours per week this would be and what the pay is like?
-- This is a temporary RA position, with work hours estimated to be 0-10 hours per week (yes, some of the weeks we may not have any work), and flexibility in your schedule is much appreciated. We have grant support through June of 2022 for this project with an hourly rate of $28. If you can work through that time or even longer (with pay as we may be able to extend the grant or switch you to different project(s) if you are interested), which is a plus, please let us know.

Expected start date?
-- ASAP with some flexibility. Note the HR hiring process will take some time before you can start to work, but we will try to get the process done ASAP.

More information about publication.
-- This work is aimed to be published. Whether your name will be listed as co-author will depend on how much intellectually work and quality of the work, e.g. data acquisition and analysis, manuscript writing, etc., is contributed to the project.