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  1. Hello! Have any of the 2018 J-School applicants heard from the school - interviews, writing tests? It looks like that they start sending out invitations in December.
  2. Hi! Was hoping to get some advice as I make a decision on where to attend for my MSW fall 2022. I have been admitted to Berkeley, UCLA, and SDSU. I currently live in LA, and want to live in southern california long term in my career. UCLA ($25,360/year) and Berkeley ($19,968/year) are significantly more expensive than SDSU ($9,570/year), and I am leaning towards SDSU for this reason. But am not sure if the rigor/accomplished faculty at the other schools are worth paying more for. Thank you!
  3. Hi! Was hoping to get some advice as I make a decision on where to attend for my MSW fall 2022. I have been admitted to Berkeley, UCLA, and SDSU. I currently live in LA, and want to live in southern california long term in my career. UCLA ($25,360/year) and Berkeley ($19,968/year) are significantly more expensive than SDSU ($9,570/year), and I am leaning towards SDSU for this reason. But am not sure if the rigor/accomplished faculty at the other schools are worth paying more for. Thank you!
  4. Country - US but international Chinese student Undergrad Institution: Top 10 US Major: Math; Statistics GPA : 3.88/4.00 Master’s Institution: No master GRE: 155+170 (Q) +4 Didnt take the math subject Coursework (all took in my undergrad, including master and phd level courses) Statistics- All undergraduate courses are A. Also took all first year statistics PhD courses you know in any legit phd programs. Got all A(s), except A- in probability measure theory, and a pass in time series analysis (switched to pass/fail due to covid) Mathematics- All undergraduate courses are A. PhD courses took real analysis (B+, sick for the covid semester), measure and integration (a pass for pass/fail due to covid), functional analysis (A) Research experience: Methodology paper received minor revision from JMLR (top 1st journal in ML, with a very reknowned professor "citation ~50000", 1st author: Just me and the professor, did 100% percent of the work) Submitted (under review) a theoretical statistics theory to JASA (top 1-4 journal in stats) with a super famous professor (someone that everyone knows, "citation ~60000". 1st author: Just me and the professor, did 100% percent of the work) Published A patent during a summer industry research Drafting another computational biology patent (from my startup) Drafting another computational biology research manuscript (from my startup) some other summer research that resulted in APP/Posters etc. not very serious... Professional experience: Goldman Sachs quant full time for a year Tencent research intern Deloitte research intern Co-founder of biotech startup Awards: - MCM/ICM got meritorious (6% out of 14000+) for consecutive 2 years - Best mathematical research award in college math department every year - A bunch of other stuff Research Interests : 1) Computational Bio, 2) Statistical Inference Theory, 3) Dynamical System Recommendation Letters : 1)Top 1% letter (Very strong) for the 50000 citation prof. Talked about research 2) Top 1% letter (Very strong) for the 60000 citation prof. Talked about research 3) Top 10-25% (Strong) from my academic advisor prof (~17000 citation). The score is low but the letter (to my knowledge) is pretty strong. Taked about my startup and everything other than research and academic. ALSO: prove my significant GPA drop in one of the semesters was due to sickness Programs: 1) Stanford Stats, 2) Berkeley Stats, 3) Harvard Stats, 4) UChicago Stats, 5) CMU Stats, 6) UW Stats, 7) UW CS, 😎 Princeton ORFE, 9) MIT EECS What is my chance?
  5. I'm not sure which program to decide on as they both seem to be great programs on paper. The draw of UCB is that it is a 1 year program, but I don't think they touch on the fundamentals as much as an MS degree would. If anyone has any insight, it would be very helpful!
  6. I have been admitted to the statistics departments at both Harvard and Berkeley. I applied to 24 schools, so I've also been accepted to virtually all of the top 20 stats programs, excluding Stanford. My academic interests are pretty broad, but I'd like my research to be more theoretical and in the realm of probability or machine learning/deep learning, if possible. I'm also not sure if I will try to go into academia or into a research team at Google, Microsoft, Facebook, etc. I am mainly considering these two because Berkeley is so good at ML, but Harvard is a better fit in every other way (culture, location, etc.). Any advice would be appreciated! I am also happy to provide any more information.
  7. Hi Everyone, Do you guys think UIUC, Berkeley, and Northwestern might have given out all PhD admissions in Materials science for Fall 2021. I see many people getting admits and also rejects. I didn't receive any communication yet, so, is there a chance I might still be in consideration? Feel free to share your opinions. Thank you,
  8. Hello, I have both the above admits for fall 2020 which I deferred to 2021. I know Berkeley ranks much higher(#3) in Mechanical Engineering than UCSD, but I couldn't find any ranking data related to Fung Institute specifically. How will you compare Berkeley's Fung institute to UCSD's Jacobs school? Also, I will be pursuing non thesis MS at UCSD as I dont want a research oriented career. M.Eng seems a better choice but the ranking of Fung institute compared to Jacobs School, the cost of the program and lack of on campus employment during M.Eng is making me think twice.
  9. Both seem great, though highly different, options. At times, I find myself considering the schools through a Head/Heart dichotomy, where: Heart = Berkeley; Head = Princeton. This may be foolishness, but there it is. *** Princeton Pros: Better stipend, less teaching, cheaper cost of living, proximate to New York and Philly, more funding for archival research, language study, and conference travel. Princeton Cons: (Allegedly) more traditional and hierarchical, not exactly a vibrant town, smaller [possibly a pro], more self-enclosed, less pleasant weather/environment overall. AND Berkeley Pros: Beautiful area, lovely weather, more diversity (of people, ideas, environment), larger [could also be a con], more vibrant grad. student life and community, more life outside of campus, (allegedly) less hierarchical. Berkeley Cons: Worse stipend, higher cost of living, more teaching, environmentally precarious area (earthquakes, droughts, wildfires, hyper-development), less funding for archival research, language study, travel. *** Any help, advice, anecdotes, are appreciated tremendously! Thank you.
  10. Hi, need some advice! I really don't know what to make of my situation right now. Should I be elated or just downright sad? Am I being too sceptical, or just playing it safe? I received an admit from Carnegie Mellon University and the University of California, Berkeley for my PhD (Direct Entry) in Mechanical Engineering. I was given a potential research advisor for both universities and told to contact him regarding my research domain and funding. It was only upon discussing further with the profs did I realise that both the offers were without funding!! I mean, who does a PhD WITHOUT FUNDING!? That too, being an international student from India, there is no way anyone can even consider these offers! Graduate studies in itself, is way too expensive. Now, upon explaining to the department regarding the current condition, they told me to approach other professors who would have a position available. I'm doing that right now, but it doesn't seem to be going anywhere. I have applied to Purdue, UIUC, UTexas Austin and UMichigan as well, but I still haven't received any information yet. If my plan goes all south, I will be stuck making one of these mentioned things- I either choose to pursue my PhD in one of the universities and decide to search for a potential advisor and funding en-route (Very, Very risky). Or, I request the university to convert my admit to an M.S program (unfunded) and think of a PhD later on (Not sure if possible in the first place). Any advice?
  11. I am currently considering between these choices: - UC Berkeley Mechanical Engineering (Product Design/ Controls) [https://me.berkeley.edu/graduate/meng/] - Penn Robotics [https://www.grasp.upenn.edu/academics/masters] - Cornell Engineering Management [https://www.engmanagement.cornell.edu/em] My background is in Mechanical Engineering from a top 5 undergraduate school. Mainly hope to develop a deep specialization in robotics, controls, design for manufacturability, hardware systems development on the technical side, and take 2-3 management courses from the business school. Highly interested in technology entrepreneurship and have attended programs/ started companies previously. If any current students or prospective students can share your opinions, it would be incredibly helpful!
  12. Hi guys, So that's the question. I am doing a PhD in architecture history and theory and have been admitted in both programs. Any inside from the departments? What would you recommend or not? I am an European applicant so do not have much information before hand.... Any info is welcomed! Thanks !
  13. I (international student) got accepted into these two programs, which are quite different, but I believe both could lead me to a good position as a data scientist, in the US preferably. I am struggling to make a decision. On the one hand, NYU's 2-year Master is a top-10 program in the subject that would allow me to dive deep into data science core subjects as well as to do an internship during the summer. I feel that I would learn a lot in this program, get to know a commnity that is doing cutting edge work on the field and, hopefully, access good job opportunities The program is expensive, though, and I have not received any financial support. On the other hand, Berkeley's 1-year program combines technical courses with business-oriented topics. This means there will be considerably less time to invest in pure data science work. IEOR is a very broad area but ideally I would specialize on analytics, which could get me closer to the kind of jobs I want. I know MEng alumni have pursued careers in data science and similar positions before. Of course, this program has Berkeley's amazing prestige and faculty behind it, plus a lot of networking oppportunities. Besides, it will be significantly less expensive than NYU's MS, since this is a one year program and I have been awarded a $16k grant. Any thoughts on making a decision? Thank you!
  14. Hi, Has anyone or their mother heard back from UC Berkeley's MPH Program? I applied under Health and Social Behavior, still waiting, and I'm wondering if I have anyone in the same boat with me.
  15. Goals/Interests: Econometrician/Biostatistician, or a Statistician/Data Scientist with domain/research focus in the biotech venture capital industry. (Or, some ‘correct’ combination of these or related labels that might be more appropriate…) Beyond market/industry research, I would also like to focus on understanding the underlying statistical methodologies and techniques being applied in medicine/biotechnology/health science (i.e. machine learning's application etc. etc.…) My goal is to convince a biotech venture capital firm that they could benefit from employing a statistician/data scientist with these particular domain interests/research experiences. Ideally, I would love to have experience on the funding side of early stage start-ups in the hopes that I could build on my academic + industry experiences in order to one day veer down an entrepreneurial path of my own (…ideally in the biotech sphere) Location: Ideally VC firms in 1. NYC, 2. SF or LA (or… firms with a combination of both NYC and a California location…) Also, I want to note these are my “perfect-world/have-my-cake-and-eat-it-too” scenarios. I recognize they are lofty Should note, re-evaluating obtaining a PhD at some point in the future would not be unthinkable (especially if it might tie in well with the other above-mentioned goals) On a side, I feel I have a decent tie back to NYC having interned in the city, and having completed the course-work equivalent of Columbia University's major requirements in their joint Mathematics-Statistics major. (Completed through a non-degree post-baccalaureate program after graduating with a degree in economics from a separate institution). I mention this as I am not sure whether Berkeley or Duke has higher employer standing in NYC...and whether or not it will matter given I already have (what I think) is already a decent tie back to the city Berkeley States the program prepares for industry rather than PhD One year Capstone: team-based learning experience on real-world problem I think strong industry placement Incoming class of 40 No financial package, mention of guaranteed research assistant positions, or internship requirement I would assume because the program is so short/condensed Duke: States the program is attractive to industry employers and for bridging to Ph.D. 2 years Financial package, guaranteed TA and RA positions, required thesis or portfolio of work, required internship Bootcamp orientation Research Assistant-ship may or may not be used in thesis requirement Incoming class of 40 Alumni review: statistically rigorous, globally recognized faculty, Bayesian and ML approaches, modeling and computation (creates better career options), small class size, class projects with real data, in-house career counseling and advising, collaborative and collegial environment Areas: PhD/Research, Data Science, Health Data Science, Finance & Economics, Marketing Research and Business Analytics, Social Science & Policy Formal Mentoring in the first year (faculty) meet once a month 3 faculty serve as advisory role, at least 2 full-time primary faculty in Statistical Science, 1 committee chair Admission statistics look very similar to Berkeley’s Strong Industry and Academic Placement My intuition: Duke is a better fit. I feel two years would be ideal in gaining the technical skills + research experience + internship experience I am seeking (and I am not in a break-neck rush) It seems there is more emphasis on mentor-ships, and on academic + career development Prestige in industry seems equivalent at Masters level (maybe Duke is ‘winning’?) Prestige in academia – at the Masters level – seems 'Duke > Berkeley' Duke seems to be slightly more expensive on an annual basis (after factoring in the financial package offered) (however, I would be paying twice as much as I would for Berkeley in total because I would be paying for the extra year at Duke that I already desire…which ultimately is OK with me) Question/Advice: Any advice, thoughts, questions on anything mentioned would be greatly appreciated! Or, if you know of anyone that might be worth speaking to, please PM me! The Big Q: Am I wrong in assuming that Duke is the clear choice for me given the goals I’ve mentioned? Is there something I am completely missing about Berkeley that I should be taking in? Or, is my take utterly wrong in every possible way 🤣😅) Other relevant Threads: https://forum.thegradcafe.com/topic/89766-ucb-vs-duke-vs-yale-vs-usf-analytics/ Duke vs. UCB vs. Yale vs. USF Masters https://forum.thegradcafe.com/topic/39107-stats-program-by-tiers/ (Not sure if this by master or PhD? If it was mentioned in the thread somewhere and I missed it, then I apologize!)
  16. I've been given interviews for the Bioengineering Program at UC Berkeley-UCSF and the Systems, Synthetic, and Physical Biology program at Rice University. Does anybody know anything about these two programs? I'm specifically thinking about the quality and relevance of their synbio research output, as well as any comparisons of the programs themselves. I'm also worried about the housing situation for grad students at berkeley, as well as grad students being way overworked. Does anybody know what its like to work for Jay Keasling or Adam Arkin in particular? I know they are big names, but Im wondering what the lab environments are like.
  17. Did any international student get admit from the UC Berkeley's Chemical Engineering - PDP program ? If yes, please share when did you get the admit and did the portal status change ? Does anyone know if the admissions are in waves or it's a one shot process ? Previous years applicants, please help.
  18. Can someone please help in providing me the questions that are asked on the interview and also their answers in key points? It would be a great help!
  19. Is there anyone who got interviews from POIs? I saw plenty of interview postings last year, but not nowadays... Does the interview indicate admission for UCB? (I mean being interviewed = high possibility of admission) Also, when will the results come out?? It's really painful to wait
  20. I've been looking around different phd programs that have a focus area in synthetic biology research, and have really like two programs in particular, namely the Bioengineering Program at UC Berkeley-UCSF and the Systems, Synthetic, and Physical Biology program at Rice University. Does anybody know anything about these two programs? I'm specifically thinking about the quality and relevance of their synbio research output, as well as any comparisons of the programs themselves.
  21. (1)Third year CS major in a US university(on the boundary of top 20...), will apply for PhD during my senior year (2)Took GRE once during my second year, and got 160 on reading, 168 on math, and 3.5 on writing (2)Expected GPA during application:3.75/4(our school doesn’t have grade inflation) (3)Since I’m interested in theoretical CS, I’ve taken a lot more upper division math classes than required, and a few CS grad classes related to my area of interest(got As in all of them) (4)One year of research experience(no publications yet), 1 internship experience (5)Will get 1-2 strong recommendations from big names in my interested field (6)Haven’t even thought about the SOP yet. Any suggestion on how to start is welcomed! Honestly what do you think is my possibility of getting into my top tier schools(e.g. Stanford, MIT, CMU, Berkeley) and lower tier schools(e.g. UWashington, Umich, Cornell...)
  22. How is the application reviewed in the interview phase of EECS MS/PhD at UC Berkeley? If interviewed and accepted into the program, would the interviewer (by default) be the PhD supervisor? Or, is the student first accepted into the program and needs to find a research supervisor later? If the students are first accepted into the program and not by a specific advisor, how would funding be handled?
  23. Hi everyone, Has anyone applied for the UC Berkeley online MPH for the spring semester? If so, what were your GRE scores/GPA and have you heard back yet? Thanks!
  24. Hi Everyone! I haven't seen a Goldman thread for Fall 2018, so I thought I'd get the ball rolling -- as well as try to offload some of this anxiety I'm feeling waiting for more results! I applied to 9 schools, mainly for MPPs, and want to study environmental policy (focusing on progressive climate adaptation/mitigation responses). I've been accepted at UCDenver and UWashington Evans so far, with a nice funding offer from the latter (which was an incredible surprise and confidence booster). Berkeley is my top choice, and I waver between feeling good about my chances and having no idea how competitive I am, which feels normal at this point in this lengthy, harrowing process...
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