I have started my PhD in statistics this year, and I am looking for your best-practices, advice and (meta-advises) regarding how to grow and become a good academic researcher in the fields of statistics/ML.
General thoughts and links are welcomed, but in order to start the ball rolling, here are a bunch of questions gathered from Michael Steele's great article "Advice For Graduate Students in Statistics" (if I am missing important questions, or if some of the questions are meaningless - please also comment on it):
- Papers vs Thesis - how much should one focus on publishing papers during his PhD work? How many papers should one realistically aspire to write?
- In what journals should one strive to get published in? (relevant questions link1, link2)
- How many hours a day should one spend on research (developing/dealing with your research question), and on learning (reading new papers/ attending courses)
- Where does one go to find "hot topic", or even better - a "soon to be hot topic"? (link1, link2)
- Once a "hot topic is found" how should one balance learning the basics of many aspect of the problem, with focusing on one aspect?
Obviously these questions are VERY general, and there are many angles for thinking/answering them - I hope to read your perspective on how to think about these general issues.
Thanks in advance!