values, culture, expectations, resources
We strive for equity in science at all positions and encourage advocacy for job stability, competitive salaries and benefits, and we do not believe in unpaid work.
Be passionate and curious, enjoy science and pursue what truly moves you.
Distinguish yourself by being a good person. A good work atmosphere is important for all to be happy. In case of conflict, try to talk with others, usually problems come from misunderstandings not from people not acting with good faith. We are more productive working together. Think about each other as teammates rather than competitors, both between and within labs. Be a giver (see this ted talk).
Everyone experiences impostor syndrome during their career, at some point or another. Remember that you belong in science, and in this lab. Reach out to your peers for support.
Never stop learning. Take time to learn things that might require a loss of immediate time, but also will pay off. When you learn something, new possibilities are generated.
READ. You need to know the state of knowledge to be able to contribute to science in a relevant way. There are some papers that you have to read in depth, for instance when you are applying the same method or theory. Most can be read superficially to get a grasp. Search the internet for new papers everyday. Platforms such as twitter or subscriptions to e-mail lists of journals help with this.
GROUP and PROJECTS
Prioritize. Learn to say NO when you don’t have time. Make sure to leave time for important tasks that don't seem very urgent (example, reading papers).
Look at the big picture when designing projects and think about finding new connections in the world of ideas. BE CREATIVE and THINK BIG - dare to question.
Discuss a lot. The more times you share your results, the more fluent you will be. It also helps to identify weak spots of your science and to see new points of view that could be the origin of the next idea/analysis.
Generate robust science: solid experimental designs, datasets, methods. This also goes together with being tidy and having reproducible results. It is time well-spent. You will get criticism, you will have to reanalyze. Doing the above, at the end will pay off.
You will make mistakes, but what you do when you make a mistake is what counts. When you discover an error, whether it's the initial results of a project or 10 years after publishing, you should be truthful and own the mistake. Take the steps it requires to fix the mistake, be it rewriting the code or submitting corrections / retractions. Be grateful for those who helped you catch the mistake as they're helping make your science even better.
The counterbalance of the above: “perfection is the enemy of progress”. It is important to do things well, but we cannot get lost in perfecting details continuously. It is important to reach a right balance with the above. If you are unsure of what to do, talk with colleagues.
Don't be afraid to start side projects. For example, develop a small test, try something out of curiosity, collaborate in something crazy with a friend, read about a very different topic. You never know when inspiration will strike.
When reviewing/hearing other people’s work remember to be skeptical, but do not be so only for the sake of being a skeptic. Note that who produces the work (paper, presentation) might have more experience and knows the data better than you. Be polite and if something does not fit, ask nicely or make kind suggestions.
PUBLISHING and SHARING
Diversity Equity Inclusion Belonging
We strive to be a team of wonderful colleagues without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or age. We believe in the value of diverse thinking, in initiatives to promote inclusion, and in a caring lab culture to achieve equity. Some resources [continuously expanded] to achieve this aim:
- Changing Culture and Climate initiative of Plantae https://plantae.org/education/changing-culture-and-climate/#mission-statement
- Anti-Racism resources bit.ly/ANTIRACISMRESOURCES
Important link between the origin of statistical genetics and racism (eugenics) https://genestogenomes.org/understanding-our-eugenic-past-to-take-steps-towards-scientific-accountability/
Important misuse of genetics research by racists http://ewanbirney.com/2019/10/race-genetics-and-pseudoscience-an-explainer.html
Carnegie has a dark history of involvement in eugenics research with the Genetics Department of Cold Spring Harbour. While this research was de-funded in 1939, it is important we are informed about this and denounce it. An important public statement of Carnegie President on the eugenics history: https://carnegiescience.edu/node/2654.
- LGBTQIA+ in STEM https://lgbtq.asee.org
- Women in STEM https://www.awis.org
Mental Health resources
- Stanford offers professional help and resources: https://vaden.stanford.edu/health-resources/mental-health; https://vaden.stanford.edu/caps/referrals
Get advice in any conflict or report violations of conduct
We denounce any kind of discrimination or violence, verbal or physical, and aim to provide resources when conflicts arise or to report misconduct.
- Every member of our lab and community has access to independent, confidential, and impartial Ombuds: https://carnegiescience.tequitable.com/#/. Ombuds are trained professionals who can help you from having confidential conversations about improving communication skills to reporting misconduct.
- Again, violence of any kind, verbal or physical, is not tolerated. To make an official report go to: https://mycarnegie.carnegiescience.edu/policy/hr-policies/violence-workplace .
You are not expected to come into the lab on weekends or holidays. We all need time off.
Be respectful of your labmates work-life balance when using Slack or emails during those times.
In fact, there are no precise hours you are expected to keep. As long as you are getting your work done you can do it at whatever time of day you like. One of the benefits of academia is having flexibility in your work schedule. In this vein, you are welcome to work ‘off campus’ when desired (i.e from home, a coffee shop etc). Chatting and working in person is one of the most enriching and motivating parts of our work, so we aim to overlap ~10 am - 2 pm.
You are however expected to regularly attend the standard weekly lab events.
Prepare a few minutes introduction/update on your project with a few bullet points on our group meeting doc (if you have new results you can add a couple of slides here). Discussions on interesting papers related to your project are very welcomed.
It is OK if plots and data are not publication ready, we want to see raw data and logical discussions.
✔ If something is important and has a firm deadline it is crucial to tell your collaborators and people, whose help you need. You should tell the relevant people the deadline as soon as you know when it is and make sure to remind them as the date approaches. This also means you shouldn’t be afraid to ‘bug’ someone about it.
✔ If something has a hard deadline for me, give me at least *one weeks’ notice* to do something that doesn’t require a lot of time (e.g. reading a conference abstract, filling out paperwork). If it requires a moderate amount of time (e.g. letter of recommendation, award nomination) give me at least *two week's notice*. If something requires multiple multiple back-and-forth interactions (research statement, teaching statement, grant/fellowship application) it would be best to have a *draft at least three weeks* before the submission deadline.
To give you a sense on the time this takes (that I need to find somewhere in the week’s schedule)
- A paperwork/conference abstract may take 30min-1h.
- A good letter of rec or nomination would take ~3h.
- A fellowship/grant review (one round) can take half/one day, depends on the topic/length/round of review. 2-3 rounds of review would be ideal for important fellowships/grants, but we also may need brainstorming meetings about the topic, questions, structure.
DATA/LAB MANAGEMENT AND REPOSITORIES
It is extremely important to keep a carefully documented laboratory book or code. For that, the lab will mainly use Gdocs (although we can use https://benchling.com/ if helpful) and for dry lab we use http://github.com (see guides subpages).