Should I apply more on Masters side and reduce the Ph.D. side?

[NLPNinja]

Hi everyone, 

 

This is my first post in this forum, so if I make any mistakes, please point it out. 

I'll go straight to the point. I'm an undergraduate majoring in software engineering at a 2-tier university in China. I'm applying for a natural language processing Ph.D in computer science. 

 

I've done a three month internship on NLP in Canada. I have no publication yet. 

 

I initially wanted to select ten 1-tier universities for PhD applying and five 2-tier universities for masters. And these PhD programs are all NLP oriented. I go to masters for general machine learning.  

 

However, given my background, I am not competitive to other applicants who have published tons of papers. And I don't want to go to a 2-tier school for PhD (only 1-tier schools has NLP research labs). So, should I reduce the number of PhD schools I select, and add more to my master selection? I mean, masters are easier to get into. And after I finished master, I could then consider going to a nice 1-tier PhD program. 

 

Will this plan in my mind work? And by the way, if you know any 2-tier universities that do have NLP labs, please tell me in your reply. Thanks!

[compiler_guy]

If you have extra money to spare, and you are not in a hurry to get your PhD, yes your plan will work. However, be sure to aim at master programs that have research opportunities for master students.