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Here are my 12 guidelines for data exploration and analysis with the right attitude for discovery:
— Itai Yanai 💔 (@ItaiYanai) 2023年1月10日
1. You never really finish analyzing a dataset. You just decide to stop and move on at some point, leaving some things undiscovered. 🧵
How to become a SUCCESSFUL academic: a guide 1/n
— Maarten van Smeden (@MaartenvSmeden) 2021年1月16日
This is how I advise my #PhD students to write research manuscripts (in case someone finds it helpful).
— Andrew Akbashev (@Andrew_Akbashev) 2023年8月29日
General points:
1. Research questions addressed by your manuscript are key and should guide you.
2. Don’t view your manuscript as an article. See it as a STORY.
3. Pick the…
In the LLM-science discussion, I see a common misconception that science is a thing you do and that writing about it is separate and can be automated. I’ve written over 300 scientific papers and can assure you that science writing can’t be separated from science doing. Why? 1/18
— Michael Black (@Michael_J_Black) 2022年12月3日
1. Inspired by @BiophysicalFrog insightful comments about the lack of training in science in how to be a PI I wanted to share some thoughts about something that helped me a lot over the years in my own learning journey. This is a thread about PI Superpowers!
— Tanentzapf Lab (@TanentzapfLab) 2019年3月13日
- 技術者が研究職をするうえで考えること
