Posts about scientists at work

Computer Science PhD Overview

A nice overview by Mor Harchol-Balter at Carnegie Mellon University on Applying to Ph.D. Programs in Computer Science:

A Ph.D. is a long, in depth research exploration of one topic. By long we’re typically talking about 6 years. By in depth we mean that at the end of the Ph.D. you will be the world expert or close to it in your particular area.

In contrast, a Ph.D. program typically requires typically less than 10 courses during the entire 6
years (at CMU there are 5 required “core” courses, and 3 required “electives”). The emphasis in the
Ph.D. is not on classes, but rather on research.

If you choose to be a professor at a research university, your life will consist of the following
tasks: (i) doing research on anything you like, (ii) working with graduate students, (iii) teaching
classes, (iv) applying for grants, (v) flying around to work with other researchers and to give talks
on your research, (vi) doing service for your department and school (like giving this talk). Note that
I say “your life” rather than your job, because for new faculty, your life becomes your job. It’s a
fantastic job/life for me because I love these activities, so I’m happy to work hard at all of them, but
it’s not right for everyone.

The document also offers a list of fellowships including: the NSF Graduate Research Fellowship and NDSEG Graduate Fellowship (disclosure: I work for ASEE administering part of the process for these, and other, fellowships – this blog is my own and not associated with ASEE).

Related: Curious Cat Science Fellowships and Scholarships directoryASEE Fellowships DirectoryScience and Engineering Doctoral Degrees WorldwideWorldwide Science and Engineering Doctoral Degree DataResearch Career in Industry or Academia

Young Geneticists Making a Difference

Young Geneticists Making a Difference

After an early phase of discouragement, Johannes Krause was able to follow his long interest in genetics and even link it to another passion of his, paleoanthropology. Krause initially chose to study biochemistry at the University of Leipzig. But “I was almost about to quit” at the frustration of learning much more about basic chemistry than biology, he says. However, in the third year of his bachelor’s degree, he took some specialised courses in genetics as an Erasmus student at the University College Cork in Ireland that revived his interest for the field.

Back in Leipzig, a summer internship on comparing gene expression between humans and chimpanzees at the Max Planck Institute for Evolutionary Anthropology sparked Krause’s enthusiasm for good. He stayed on in the lab as a research assistant for 2 years before graduating in 2005. While there, Krause helped develop a biological method to read large pieces of ancient DNA, sequence the complete mitochondrial genome of the mammoth from fossil samples, and place it in the context of evolution. “Johannes has great technical skill and the judgment to distinguish a good project from a blind alley. Like few others he can see the interesting pattern that can hide in sometimes confusing data,” Svante Pääbo, his principal investigator, writes in an e-mail to Science Careers.

Related: posts on science and engineering careersscience internshipsengineering internshipsNSF Graduate Research Fellow Profiles

Great Speech by Marissa Mayer on Innovation at Google

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Marissa Mayer speech at Stanford on innovation at Google (23 minute speech, 26 minutes of question and answers). She leads the product management efforts on Google’s search products- web search, images, groups, news, Froogle, the Google Toolbar, Google Desktop, Google Labs, and more. She joined Google in 1999 as Google’s first female engineer. Excellent speech. Highly recommended. Google top 9 ideas:

(inside these are Marissa’s thoughts) [inside these are my comments]

  1. Ideas come from anywhere (engineers, customers, managers, executives, external companies – that Google acquires)
  2. Share everything you can (very open culture)
  3. Your Brilliant We’re Hiring [Google Hiring]
  4. A license to pursue dreams (Google 20% time)
  5. Innovation not instant perfection (iteration – experiment quickly and often)
  6. Data is apolitical [Data Based Decision Makingcommon errors in interpreting data – read the related links too]
  7. Creativity loves Constraints [process improvement and innovation]
  8. Users not money (Google focuses on providing users what they want and believe it will work out)
  9. Don’t kill projects morph them

So far every time I hear one of Google’s leaders speak I am happier that I own a bit of stock – this is another instance of that.

Related: Technology Speakers at GoogleGoogle’s Page urges scientists to market themselvesInnovation at GoogleAmazon InnovationScience and Engineering Webcast directoryEngineers – Career Options

Second Life for Scientist

A farewell to academia and hello to Second Life – a professor of Physics and Astronomy moves on the the second act of his professional career.

Loved the teaching. Loved the science. Couldn’t take the politics. Couldn’t take the tenure stress. That about sums it up.

It is a very good post that spells out several important points that should be addressed including:

Many people have noted that it’s getting harder to get null results published, and that it’s very difficult to get “credit’ for having done good science if you produce a null result… even though such things really should be the bread and butter of what scientists do, if we really believe all the things we say all the time about how science works, and about how the process of science is an honest, open, and objective process.

Related: Research Career in Industry or AcademiaThe World’s Best Research UniversitiesSo, You Want to be an Astrophysicist?

A Career in Computer Programming

Why a Career in Computer Programming Doesn’t Suck (A Response)

Programmers need to be lifelong learners. I’m not sure what else to tell you. Lots of people change their professions. It’s not too late for you. Alternatively, you could find a job using a stable technology that you enjoy. Maybe you should find somewhere that will let you use C or C++, both of which are unlikely to disappear anytime soon.

To the readers, pick a field that’s compatible with your own nature. You’ll be much happier. If you find that you’ve chosen the wrong field, change it. It’s just a job. Find something you actually enjoy, even if it means a massive career change. It’s better to be poorly-paid and happy than highly-paid and miserable.

Related: Hiring Software DevelopersWant to be a Computer Game Programmer?Engineering Graduates Get Top Salary Offers (CS is close)

So, You Want to be an Astrophysicist?

Dynamics of Cats (good name don’t you think) has an interesting series of posts: So, you want to be an astrophysicist? The latest is: Part 2.5 – grad school by Steinn Sigurðsson:

Think very seriously about whether you want to do theory, observation, data analysis or instrumentation.
You may end up doing things you never imagined out of necessity (like theorists go take observations, cause if they don’t no one else will; or observers running simulations, or building the instrument they need to do the observations etc etc).

Finally: READ!!! Pro-actively.
Check arXiv regularly and thoroughly. Read the papers relevant to you and anything else that looks interesting.
Read the references! They are there for a reason. Read the citations – if a paper is interesting, papers which cite it are also likely to be interesting. Use the ADS “C” option liberally and look through it quickly. If in doubt ask you advisor, or just read it anyway.

Next, the slightly tricky issue of what we actually “do”, research wise type of thingy. Might take a while… is a (even the) great open access article resource. “Open access to 400,419 e-prints in Physics, Mathematics, Computer Science and Quantitative Biology.”

Research Career in Industry or Academia

In, Working in Industry vs Working in Academia, a computer scientist (software engineering) shares their experience and opinion on research career options. He discusses 4 areas: freedom (to pursue your research), funding, time and scale, products (papers, patents, products).

In academia, you’re under a huge amount of pressure to publish publish publish!

In industry, the common saying is that research can produce three things: products, patents, and papers (in that order). To be successful you need to produce at least two of those three; and the first two are preferred to the last one. Publishing papers is nice, and you definitely get credit for it, but it just doesn’t compare to the value of products and patents.

Related: post on science and engineering careersGoogle: engineers given 20% time to pursue their ideas