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Found 4 results

  1. Hello people! I am a 2018 ChemE grad from Nigeria and I'm applying to ChemE PhD programs in the US. I graduated from a top 5 Nigerian institution where I completed senior research and design projects. I was wondering if these would be sufficient research experience for PhD programs given that American and Asian students have more research experiences. My stats are: GPA--4.82/5(roughly a 3.87/4) GRE-- 160Q, 162V, 4.5 My research interests include-- fuel/PV cells, electrochemistry and batteries, CO2 conversion, and air pollution Other info-- I have LORs from my research Super
  2. After a Skype interview with a professor, she said she would get back to me by the end of the week (I am assuming about a formal in person interview) but she did not get back to me then or the week after. Is it okay if I email her and ask for an update. I know it is a no but I just wish she would formally say she is not inviting me.
  3. I completed my BS in Computer Science last year with a CGPA of 2.82. I have two publications (as co-author) at good venues. I am in the process of writing papers (as first-author) on two of my current projects, which will, unfortunately, be submitted after the current admission cycle has ended (after December). I will be taking GRE in the next month. I don't want to wait for the next year to apply and have decided to try my luck this year. My main concern is my GPA. Most schools that I have looked at have a minimum requirement of 3.0. Is there a realistic chance of getting accepted w
  4. Background- The Good: - The 3 yrs BA experience (working in the analytics field has actually inspired me to go one level deeper and transition into ML) The Bad: GRE: 319 (V:155, Q:164, AWA:4.0) TOEFL: 107 CGPA: 3.20 The Ugly: - No publications - Undergrad degree in Mechanical engineering I have completed Andrew Ng's ML course on Coursera and I have the below mentioned tasks in mind before I start my applications for Fall '17 Kaggle - Pick any of the ongoing/completed competitions and showcase the methodology/performance comparison between models on any blog
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