January 2013
4 posts
5 tags
5 tags
"Please consider not doing a PhD." →
astronomnomy:
-“Liv”
Please read it all, including the comments if you can! Choice quote, I really agree with it, and it can sneak up on you:
“Doing a PhD will break you. It’s pretty much designed to break you.”
I also agree with this blogpost fully. A success story that is as realistic as one will find in academia. Vital advice. Use it.
7 tags
We are not simply stardust...
I’ve seen that Lawrence M. Krauss “… You are all stardust. You couldn’t be here if stars hadn’t exploded, because the elements - the carbon, nitrogen, oxygen, iron, all the things that matter for evolution - weren’t created at the beginning of time…” quote being bandied about and I need to say a couple of things about why that’s not entirely true. Sorry.
Now,...
7 tags
“The Administration shares your desire for job creation and a strong national...”
– Paul Shawcross (Chief of the Science and Space Branch at the White House Office of Management and Budget) in response to the online petition by the US electorate to build a Death Star.
October 2012
3 posts
6 tags
“If you are counting how many hours a week you are working, you probably don’t...”
– Lucianne Walkowicz on distilling the advice from the now infamous e-mail to astronomy graduate students at Arizona State University. The quote above is near enough the advice I gave a bunch of starting PhD students, at the STFC PhD Intro to Astronomy Summer School in September, except in far more...
4 tags
The detection of interstellar boron sulfide: A... →
astronomnomy:
Aimed at grad students/one-day grad students - this email encompasses a mentality in the field that you may have to deal with. Be warned.
jjcharfman:
Does everyone remember the famous letter from Caltech chemist Erick Carreira to his unruly, unmotivated, and apparently unprincipled laboratory assistant? Or subsequent discussion about the compulsory workaholic culture of academic...
3 tags
July 2012
2 posts
5 tags
6 tags
June 2012
1 post
4 tags
Watch the transit of Venus live on the UQ website →
smashtronomy:
parkysnewbrain:
Tomorrow Venus moves in front of sun (or ‘transits’), and Brisbane is perfectly placed to observe both the ingress and egress of the transit. If you miss it, the next transit is in 2117, so the chances are you won’t be alive to see it. However, if you don’t live in Australia, we have a telescope linked to a camera, and will be streaming the transit over the web. ...
May 2012
6 posts
5 tags
4 tags
“The [academic] job market is brutal, we all know that. Grad school is a gamble,...”
– boiler (via isomorphismes)
8 tags
Publication bias
This is almost common sense but if you can characterize it by value - excellent! The simple statement is that things that are found in data are more likely to be published than things that are not found.
For example, if a scientific paper finds (cosmology hit again) non-gaussianity in the CMB it is more likely to be published than anything that doesn’t find non-gaussianity (if judging by...
8 tags
Massive black holes halt star birth in distant...
astronomnomy:
This is the full press-release (sans contact details) for the new HerMES consortium Nature paper led by Dr Mat Page of MSSL. I’m putting the full one up for those interested, doing it as two separate posts to get the tl;dr one with the picture out. (PS, Can you tell I’m somewhat invested in the HerMES consortium?)
Astronomers, using the European Space Agency’s (ESA) Herschel Space...
6 tags
Markov chain Monte Carlo
Briefly… I want to only touch on Markov chain Monte-Carlo (MCMC) simulations. To explore probabilities of multiple parameters (probability-space) is computationally expensive. If you, say take 10 variations of a single parameter that will cost 10 computations. Two parameters will cost 100 computations. If you, say, compute 8 parameters, it will cost 100,000,000 evaluations. Supercomputers...
6 tags
Model Selection with Bayes Theorem
The purpose of data analysis is to work out whether the values of parameters are compatible with data. By parameters, I mean some measurement(s) that has been created by theory or past experiment. During model selection, one may ask what parameters are indicated by the data. In combining these two analyses, one can create a feedback loop that simultaneously tests how well a theory fits a set of...
