kimstatistics

Hi, this is PhD student from same country with you at 30ish school. I saw your another post at different website too. I hope I can help you with if possible. I think you still have a chance to get in 30ish or even higher(cannot guarantee but worth to try). You did well in your masters and hopefully it can compensate your low undergraduate GPA. Of course the student with high GPA from prestigious school will be the strong applicant, but other than that some schools give more weight to the name of school compared to high GPA, and other schools prefer high GPA even though they are not coming from top schools(at least okay school though). It depends on the admission committee of each school, but former case is my department based on examples I saw even though I'm from unknown school. As Stat Assistant Professor already mentioned, I also recommend you to apply wide range of schools. Admission procedure has a lot of uncertainty. I know it would be costly, but you can spend that money for your dream. Besides the information from Stat Assistant Professor, I would like to say you can find the list of PhD student at each department's website, and you can see that they are favorable to korean or not. I know a few schools that they've (almost) never accepted korean.

Thank you for your answers. I'm sorry saying too broad and unclear. It is uncertainty quantification using computer experiment. What I concern is this field is too small and has less job opportunity or not, it may not be true though. Also I cannot get this field is big or increasing. Someone said this field is not super popular in this big data generation but have become increasingly popular in the past two decades. I would really appreciate any advice.

Hi, I'm 1st year phd student in stat/biostat. Since I don't have enough knowledge about fields in statistics, I would like to ask you some advice for choosing my research interests even though this can be silly question. I don't have a specific interests until yet, but I hope it can be applied in various fields and have enough positions in academia. High-dimensional data analysis(including functional data analysis) and uncertainty quantification(using gaussian process) come to my mind among available options. High-dimensional study is very popular now and many statisticians do this. I guess this is in high demand but also common and more competitive. On the other hand, uncertainty quantification is pretty unfamiliar to me. I think it lies in Statistics and Industrial engineering and this can be advantage. However, it is not easy to find TT faculty in this field rather than high-dimensional study. In addition, I've heard time series is on the decline recently. Is it really on the decline? and Does it have many job opportunity especially in academia? I know all of these are depends on my publications, but I want to know general trend. It will be better option if there is something combined with these two fields, but I cannot imagine anything yet. I really appreciate your advice or answers in advance!