How to leave academia (for science PhDs)

Post by VMG » Thu, Apr 05, 2012, 7:36 PM UTC

yummyfajitas wrote: post #57

VMG wrote: post #53

Earlier quoted context omitted.

I think this is more slightly more on-topic as a reply here > Consider the integers from [0,1000]. Suppose a particle starts at position n. At discrete instants of time t=0,1,2,…, the particle moves up or down with p=0.5. What is the probability that the particle reaches 0 before t=1000? The answer is 50%, right? I can't explain it properly, but my thinking is that the random walk is symmetric and 0 and 1000 should h…

The particle doesn't necessarily start out in the middle.

Post by graphene » Thu, Apr 05, 2012, 7:37 PM UTC

dxbydt wrote: post #68

graphene wrote: post #64

Earlier quoted context omitted.

shouldn't that be {123, 213, 312, 321}? ie 231 is not possible since after 1 randomly decides to sit at 3, 2 has no reason to go sit in seat 1. This doesn't change the answer to the problem though I think.

uh, nope. xyz => 1 sits on seat x, 2 on seat y, 3 on seat z So the only possibilities are: 123: 1 sits on seat 1, 2 on seat 2, 3 on seat 3 213: 1 sits on seat 2, 2 on seat 1, 3 on seat 3 231: 1 sits on seat 2, 2 on seat 3, 3 on seat 1 321: 1 sits on seat 3, 2 on seat 2, 3 on seat 1 passenger 3 is happy twice out of 4, hence 50% In the code, the happyLast variable counts the number of times the last passenger is happy…

Post by dxbydt » Thu, Apr 05, 2012, 7:45 PM UTC

VMG wrote: post #53

robertskmiles wrote: post #25

> 100 passengers have queued up to board a plane, and are lined up in the order of the seats on the plane (n=1..100). However, the first person lost his ticket and selects a random seat. The remaining passengers will occupy their assigned seat if it is available, or a random seat otherwise. What is the probability that passenger 100 sits in seat 100? It really worried me that I couldn't figure out how to work that ou…

I think this is more slightly more on-topic as a reply here > Consider the integers from [0,1000]. Suppose a particle starts at position n. At discrete instants of time t=0,1,2,…, the particle moves up or down with p=0.5. What is the probability that the particle reaches 0 before t=1000? The answer is 50%, right? I can't explain it properly, but my thinking is that the random walk is symmetric and 0 and 1000 should h…

     object particle {
       def main(args:Array[String]) = {
         val simulations = args(0).toInt
         val rng = new util.Random
         val reachedZero = (1 to simulations).map(_=> {
           var t = 0
           var z = 1+rng.nextInt(1000)     
           do {
             z += {if (rng.nextBoolean) 1 else -1}
             t +=1
           } while( z != 0 && tscala particle 1000000
      >0.024782

Post by eli_gottlieb » Thu, Apr 05, 2012, 8:09 PM UTC

sunahsuh wrote: post #69

eli_gottlieb wrote: post #59

Earlier quoted context omitted.

Do keep in mind, while we're all bashing academia, that there are those who go the opposite direction. I finished a researchy undergrad, went to industry, basically got miserable , and have gone right back to apply for PhD programs. I'm incredibly happy to know I have at least the one admission, even if it doesn't have guaranteed funding!

Just for full disclosure, I did the same, in that I did research and publication as an undergrad, worked in industry briefly and then went back to do a PhD (in my case, I had gotten in before I finished undergrad and deferred my admission to work for a bit.) Personally, I'm not bashing academia per se -- I think it's great for people with the right mix of temperament and motivation. The travesty is that so many peopl…

Post by lutorm » Thu, Apr 05, 2012, 8:14 PM UTC

jakobe wrote: post #5

narkee wrote: post #3

I'm finishing my PhD, and starting a post-doc in the fall. I had wanted to break out into industry, because I didn't see myself in academia in the long term, but I didn't get anywhere with job applications, so here I am. I have a few questions: 1. My work consumes most of my time and energy - how would one find time to work on side projects and build a portfolio, when the academic workload is so all-consuming 2. I fe…

Concerning the workload: As far as I'm concerned, the academic workload is definitely not all-consuming. From watching my colleagues, I came to the conclusion that everybody chooses their own workload. Some of my coworkers come at 9AM and leave at 4PM; others think they absolutely must finish that experiment and stay until 10PM. Some people think they must immediately rush to the lab if their supervisor sends them an…