Welcome to the lab!
This page is created for new comers to the lab.
For a quick overview of what we are up to, please check out a list of papers, projects, software and data-sets we work on in the lab.
- If you are new to Columbia and NYC, you will find some helpful information on this page, in particular housing options. For international scholars, here is a private document contributed by Gao’s group members sharing their personal experiences to provide useful information to new comers. Please request access to this document only if you are in or about to join our group; and please contribute to this document so others can keep benefiting from it – you can track change on the document and also suggest removing outdated information from others, as you update them with your latest experiences.
- You should have received onboarding instructions from the HR office prior to your start day. Please follow those to complete all the paperwork before coming to the lab in person.
- To setup your personal computing environment at the lab, you may find this section of productivity tips a useful resource.
When you get a chance, please email me (firstname.lastname@example.org) your account information for slack and github. We use slack for daily communications and quick exchange of information, and github to keep track of our research work. I will add you to relevant slack channels and github repositories.
Since we work in a highly collaborative environment, it is important that lab members are aware of and respect each other’s work style. To establish a common ground of collaboration and communication, it is highly recommended that lab members follow these 3 lab rules:
- Reproducible Research on GitHub: Please refer to this page for detailed instructions and examples of the requirements for reproducible research.
- Weekly In-Person Meetings: As a lab member, you are expected to meet with me on a weekly basis to discuss projects or educate me on topics you have become an expert on. Please note that these meetings should not be considered a status checks or a progress report, as these should be communicated via daily GitHub pull requests already prior to the meetings. Instead, use the meeting to address any outstanding questions or discuss next steps, as well as any difficulties (professional or personal) you would like my help with. If we do not have fixed weekly meetings arranged, then please take the initiative to book these meetings on my calendar. Please keep detailed notes and post action items on GitHub issues in relevant repositories as summary of meetings. During our meeting, it is highy recommended to use Juptyer Notebooks or whiteboard drawing (if we meet in person) to communicate the discussion, rather than making formal slides. If you need to meet with me urgently but cannot find a slot on my calendar, please send me a message to pencil in a meeting.
- The Slack App for Daily Communication: Please install the Slack app on your computer for instant communication on projects. Please be aware that I may message you after hours or on weekends, but you are not obligated to respond until normal business hours. I only send these messages in case I forget to send them later, and I don’t expect an immediate response if it is after hours.
For master student research assistants:
- To make meaningful progress on projects, we require a minimum of 10 hours per week during the semester (ideally 15 hours or more for senior Master’s students) and 40 hours per week during the summer, excluding vacation days, until you graduate. Most projects take over a year to complete and publish in peer-reviewed journals, so we expect long-term commitment from student researchers.
- Initially, all students will start with a non-paid position and a one-month rotation period. At the end of this period, we will evaluate their performance and discuss the possibility of continuing research in the lab. If a student demonstrates exceptional work and adherence to the lab rules for three months, they may become eligible for a stipend. However, if a student fails to reach out in person to discuss their progress for one month, they will be considered to have left the lab (with exceptions for communicated absences).
- Here is a general expected timeline of your progress that leads to a first-authored or co-authored publication, although the case of each student could be very different:
- Year 1: late September - late October: rotation project.
- Year 1 November - Year 2 April: assist a senior postdoc or student to complete their project, while conceiving & conducting some of your own project.
- Year 2 May - September: make substential progress at your own project.
- Year 2 September - December: for those looking to apply for a PhD program it might help to draft a preprint of the manuscript if possible.
- Year 2 September - Year 3 May: finish up your project with a complete manuscript drafted; if possible work on another collaborative project with others in the lab to contribute to another publication.
- For those intended to use our work for the Biostatistics Practicum project, you must send me the write-up for comments before submitting it to the Department of Biostatistics.
- I will only provide strong reference letters for PhD program applications if you reach some milestones I have set at the early stages of your research projects, including but not limited to reaching the publication goal.
In principle, we offer the competitive paid research assistant position to only very capable students (comparable to those who currently receive a stipend in the lab). Since our goal for Master’s students is to complete a publishable paper before graduation, we expect strong self-motivation and excellent performance from applicants. Students with these qualifications are usually rewarded with a stipend.
Explore lab wiki
In addition to some links you have previously checked out, you are encouraged to explore the lab wiki checking out material on other pages. On this wiki you should find answers to the most frequently asked questions as a new comer. In particular,
- Ask questions!
- A list of learning material on various topics in computational biology, if you wonder where to get more background knowledge for the research we conduct.
- A list of “must know” shell commands.
- High Performance Computing cluster usage and computational resource sharing guideline.