Thursday, March 23, 2023

A Strange Hiring Season

In my fall jobs post, I had trouble predicting this season's CS faculty job market but I didn't expect this:  strong supply and strong demand, something we haven't seen since the early '80s when the then young CS departments were ramping up.

We have a confluence of two forces that have both strengthened since my post back in November: The layoffs and hiring freezes at the major internet companies (Alphabet, Amazon, Apple, Meta and Microsoft) contrasted with major excitement in machine learning. I wrote the jobs post before ChatGPT was released and Amazon and Meta have since announced even more layoffs.

ML-mania is leading to very strong demand from undergrad and grad students for computing degrees. Across the US we have a record number of open faculty slots in computing as universities try to meet that need.

Meanwhile, PhDs who might have gone to industry are going on the academic job market instead. Also some tech researchers who have been laid off or spooked by the layoffs are considering academic jobs.

Between these two forces we will likely have a record number of faculty hires this year but we may see fewer senior people switching universities because good departments can fill their needs with junior faculty.

There is a mismatch of area. There is a big demand in CS departments to hire in machine learning because that is where the student interest is. ML is not where the big companies are cutting back. If you are on the market this year, position your research to make it relevant to learning, or at least that you are willing to teach ML courses.

By the way, this post is for computer science. Count yourself extremely lucky if you can get a tenure-track job in a non-computing field.

1 comment:

  1. > If you are on the market this year, position your research to make it relevant to learning, or at least that you are willing to teach ML courses.

    I hesitate to contradict Lance here, but I would strongly discourage consciously doing the first part of this (except in cases where it naturally makes sense). I've never seen a case where this worked well, and candidates run a risk of looking like they do not know what they're talking about or are fad chasing.

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