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As someone with a PhD in an engineering field (but currently working as a data scientist because all of my research was computational science), I wonder if inde

As someone with a PhD in an engineering field (but currently working as a data scientist because all of my research was computational science), I wonder if independent machine learning publications would help with getting one of these jobs or if the CS PhD from a brand name school is an absolute requirement. I have 8 publications in my field, so I’m familiar with the peer review process, and it seems that with (a lot of) time permitting it might be possible to get a couple of NIPS presentations or JMLR papers. But I don’t know if publications alone would be enough to get hired for these AI positions. I had a hard time making the decision when I chose an engineering PhD over a CS one, but 6 years ago machine learning hadn’t taken off like it has now, and engineering / hard science prospects seemed brighter at the time. If I had known it was going to become this big and this interesting, I definitely would have gone for CS instead.

throwawayjava 9y ago
> but 6 years ago machine learning hadn’t taken off... I definitely would have gone for CS instead. I thnk you're doing it wrong because that's exactly why there's so much demand for CS PhDs right now. Rewind to mid-2000's when the CS postdocs/phds graduating over the past couple of years were choosing to major in CS. They were warned that everything was being outsourced to India and advised to choose a "real" engineering field, or perhaps finance/physics/math. It's hard to imagine today, but lot of smaller colleges/universities were killing CS majors back in the mid 00's! So not only is there a shortage of CS PhDs in the pipeline, but the ones that made it through came in with a burning passion for the science (as opposed to the money/hotness). This combination of input bias and restricted supply is what makes the current labor market so damn hot. In 3 years, that will invert, and some major struggling to justify its existence because it's hard but has "no future" will blow up. Rinse and repeat.

throwawayjava 9y ago

> but 6 years ago machine learning hadn’t taken off... I definitely would have gone for CS instead. I thnk you're doing it wrong because that's exactly why there's so much demand for CS PhDs right now. Rewind to mid-2000's when the CS postdocs/phds graduating over the past couple of years were choosing to major in CS. They were warned that everything was being outsourced to India and advised to choose a "real" engineering field, or perhaps finance/physics/math. It's hard to imagine today, but lot of smaller colleges/universities were killing CS majors back in the mid 00's! So not only is there a shortage of CS PhDs in the pipeline, but the ones that made it through came in with a burning passion for the science (as opposed to the money/hotness). This combination of input bias and restricted supply is what makes the current labor market so damn hot. In 3 years, that will invert, and some major struggling to justify its existence because it's hard but has "no future" will blow up. Rinse and repeat.