CI Fellows Program, again

Are you graduating and interested in doing a fun postdoc in your area of choosing on your project of choosing?  Apply to be a NSF CI Fellow!

Postdoc Position at CLIP (@UMD)

Okay, now is why I take serious unfair advantage of having this blog.  We have a postdoc opening.  See the official ad below for details:

A postdoc position is available in the Computational Linguistics and
Information Processing (CLIP) Laboratory in the Institute for Advanced
Computer Studies at University of Maryland.  We are seeking a talented
researcher in natural language processing, with strong interests in
the processing of scientific literature.

A successful candidate should have a strong NLP background with a
track record of top-tier research publications.  A Ph.D. in computer
science and strong organizational and coordination skills are a must.
In addition to pursuing original research in scientific literature
processing, the ideal candidate will coordinate the efforts of the
other members of that project.  While not necessary, experience in one
or more of the following areas is highly advantageous: summarization,
NLP or data mining for scientific literature, machine learning, and
the use of linguistic knowledge in computational systems.
Additionally, experience with large-data NLP and system building will
be considered favorably.

The successful candidate will work closely with current CLIP faculty,
especially Bonnie Dorr, Hal Daume III and Ken Fleischmann, while
interacting with a large team involving NLP researchers across several
other prominent institutions.  The duration of the position is one
year, starting Summer or Fall 2011, and is potentially extendible.

CLIP is a a dynamic interdisciplinary computational linguistics
program with faculty from across the university, and major research
efforts in machine translation, information retrieval, semantic
analysis, generation, and development of large-scale statistical
language processing tools.

Please send a CV and names and contact information of 3 referees,
preferably by e-mail, to:

    Jessica Touchard
    jessica AT cs DOT umd DOT edu
    Department of Computer Science
    A.V. Williams Building, Room 1103
    University of Maryland
    College Park, MD 20742

Specific questions about the position may be addressed to Hal Daume
III at hal AT umiacs DOT umd DOT edu.

Graduating? Want a post-doc? Let NSF pay!

I get many of emails of the form "I'm looking for a postdoc...." I'm sure that other, more senior, more famous people get lots of these. My internal reaction is always "Great: I wish I could afford that!" NSF has a solution: let them pay for it! This is the second year of the CI fellows program, and I know of two people who did it last year (one in NLP, one in theory). I think it's a great program, both for faculty and for graduates (especially since the job market is so sucky this year).

If you're graduating, you should apply (unless you have other, better, job options already). But beware, the deadline is May 23!!! Here's more info directly from NSF's mouth:

The CIFellows Project is an opportunity for recent Ph.D. graduates in computer science and closely related fields to obtain one- to two-year postdoctoral positions at universities, industrial research laboratories, and other organizations that advance the field of computing and its positive impact on society. The goals of the CIFellows project are to retain new Ph.D.s in research and teaching and to support intellectual renewal and diversity in the computing fields at U.S. organizations.
.....
Every CIFellow application must identify 1-3 host mentors. Click here to visit a website where prospective mentors have posted their information. In addition, openings that have been posted over the past year (and may be a source of viable mentors/host organizations for the CIFellowships) are available here.

Good luck!

Blog heads east

I started this blog ages ago while still in grad school in California at USC/ISI. It came with me three point five years ago when I started as an Assistant Professor at the University of Utah. Starting some time this coming summer, I will take it even further east: to CS at the University of Maryland where I have just accepted a faculty offer.

These past (almost) four years at Utah have been fantastic for me, which has made this decision to move very difficult. I feel very lucky to have been able to come here. I've had enormous freedom to work in directions that interest me, great teaching opportunities (which have taught me a lot), and great colleagues. Although I know that moving doesn't mean forgetting one's friends, it does mean that I won't run in to them in hallways, or grab lunch, or afternoon coffee or whatnot anymore. Ellen, Suresh, Erik, John, Tom, Tolga, Ross, and everyone else here have made my time wonderful. I will miss all of them.

The University here has been incredibly supportive in every way, and I've thoroughly enjoyed my time here. Plus, having world-class skiing a half hour drive from my house isn't too shabby either. (Though my # of days skiing per year declined geometrically since I started: 30-something the first year, then 18, then 10... so far only a handful this year. Sigh.) Looking back, my time here has been great and I'm glad I had the opportunity to come.

That said, I'm of course looking forward to moving to Maryland also, otherwise I would not have done it! There are a number of great people there in natural language processing, machine learning and related fields. I'd like to think that UMD should be and is one of the go-to places for these topics, and am excited to be a part of it. Between Bonnie, Philip, Lise, Mary, Doug, Judith, Jimmy and the other folks in CLIP and related groups, I think it will be a fantastic place for me to be, and a fantastic place for all those PhD-hungry students out there to go! Plus, having all the great folks at JHU's CLSP a 45 minute drive a way will be quite convenient.

A part of me is sad to be leaving, but another part of me is excited at new opportunities. The move will take place some time over the summer (carefully avoiding conferences), so if I blog less then, you'll know why. Thanks again to everyone who has made my life here fantastic.

Interviewing Follies

Continuing on the theme of applying for jobs, I thought I'd share some interviewing follies that have happened to me, that I've observed others do, and that I've heard about. There is a moral to this story; if you want to skip the stories and get to the moral, scroll to past the bullet points.

1. Missing your plane. I had an interview in a place that was about a 1-2 hour flight away. I flew out first thing in the morning and back last thing at night. Except I didn't fly out first thing in the morning: I missed my flight. Why? Because I cut flights close (someone once said "if you've never missed a flight, you're spending too much time in the airport") and the particular flight I was on left not out of a normal gate, but out of one of those that you have to take a shuttle bus to. I didn't know that, didn't factor in the extra 5 minutes, and missed the flight. I called the places I was interviewing at, re-arranged meetings and the day proceeded with a small hiccup.
   
   I ended up getting an offer from this place.
   
2. Missing a meeting. I was interviewing at a different place, going through my daily meetings, got really tired and misread my schedule. I though I was done when in fact I had one meeting to go. I caught a cab to the airport, flew back home, and noticed a few frantic emails trying to figure out where I was (this is before I had an email-capable cell phone). (As an aside, someone once told me that they would intentionally skip meetings on interview days with people outside their area, figuring that neither the candidate nor the interviewee really wanted such a meeting. They would hang out in the restroom or something, and blame a previous meeting running long on the miss. This was not the case in my setting.)
   
   I did not end up getting an offer from this place.
   
3. Someone interviewing here a long time ago was scheduled to give their talk using transparencies. Two minutes before the talk they realized that they had left them in the hotel room. The already-assembled audience was asked to stay put, the speaker was quickly driven to the hotel and back, and proceeded to give one of the best interview talks on record here.
   
   This person ended up getting a job offer.
4. Someone interviewing somewhere I know left their laptop in their hotel, just like number 3. But instead of having their host drive them back to the hotel, they borrowed someone's car to drive back to the hotel. They crashed the car, but managed to get their laptop, and gave a great talk.
   
   This person ended up getting a job offer.
5. I flew in late to an interview, getting to my hotel around midnight. I woke up the next morning at seven for an 8:30 breakfast meeting. I unpacked my suit, tie, belt, socks and shoes. And realized I had forgotten to pack a dress shirt. All I had was the shirt I had worn on the plane: a red graphic tee shirt. My mind quickly raced to figure out if there was a place I could buy a dress shirt in the middle of nowhere at 7am. I quickly realized that it was impossible, wore my tee shirt under my suit jacket, and went through the day as if that was how I had planned it.
   
   I ended up getting a job offer.
   

The moral of this story is that bad things happen during interviews. I can't compare any of my stories to the crash-the-car story, but we've all been there, done stupid things, and gotten through it unscathed. I think the trick is to pretend like it was intentional, or at least not get flustered. Yes I missed my flight, yes I forgot my shirt, yes I crashed your car. But it doesn't affect the rest of my day. You have to be able to relax and forgive yourself minor mistakes: the interviewers really are looking at the bigger picture.

That said, there are definitely things you can do to botch an interview. They have to do with things like giving a bad talk (my experience is that a huge weight is placed on the quality of your job talk) and not having a clear vision for where you're going in research life. Don't be afraid to disagree with people you're talking to: we usually aren't trying to hire yes-men or yes-women. Once you get a job, especially a faculty job, you are the one who is going to make things happen for you. You have a world view and that's part of what we're hiring. Let us see it. We might not always agree, but if you have reasons for your view that you can articulate, we'll listen.

But don't focus on the little things, and don't get flustered.

Some notes on job search

There are tons of "how to apply for academic jobs" write-ups out there; this is not one of them. It's been four years (egads!) since I began my job search and there are lots of things I think I did well and lots of things I wish I had done differently.

When I entered grad school, I was fairly sure that I eventually wanted a university job. During high school, my career goal was to be a high school math teacher. Then I went to college and realized that, no, I wanted to teach math to undergraduates. Then I was an advanced undergraduate and realized that I wanted to teach grads and do research. Teaching was always very important to me, though of course I fell in love with research later. It was unfortunate that it took so long for me to actually get involved in research, but my excuse was that I wasn't in CS, where REU-style positions are plentiful and relatively easy to come by (system development, anyone?).

However, the more time I spend in grad school, including an internship at MSR with Eric Brill (but during which I befriended many in the NLP group at MSR, a group that I still love), I realized that industry labs were a totally great place to go, too.

I ended up applying to basically everything under the sun, provided they had a non-zero number of faculty in either NLP or ML. I talked (mostly off the record) with a few people about post-doc positions (I heard later than simultaneously exploring post-docs and academic positions is not a good idea: hiring committees don't like to "reconsider" people; I don't know how true this is, but I heard it too late myself to make any decisions based on it), applied for some (okay, many) tenure-track positions, some research-track positions (okay, few) and to the big three industry labs. I wrote three cover letters, one more tailored to NLP, one more to ML and one more combined, three research statements (ditto) and one teaching statement. In retrospect, they were pretty reasonable, I think, though not fantastic. I don't think I did enough to make my future research plans not sound like "more of the same."

I suppose my biggest piece of advice for applying is (to the extent possible) find someone you know and trust at the institution and try to figure out exactly what they're looking for. Obviously you can't change who you are and the work you've done, but you definitely can sell it in slightly different ways. This is why I essentially had three application packages -- the material was the same, the focus was different. But, importantly, they were all true. The more this person trusts you, the more of the inside scoop they can give you. For instance, we had a robotics/ML position open (which, sadly, we had to close due to budget issues), but in talking to several ML people, they felt that they weren't sufficiently "robotics" enough; I think I was able to dissuade them of this opinion and we ended up getting a lot of excellent applicants before we shut down the slot.

Related, it's hard to sell yourself across two fields. At the time I graduated, I saw myself as basically straddling NLP and ML. This can be a hard sell to make. I feel in retrospect that you're often better off picking something and really selling that aspect. From the other side of the curtain, what often happens is that you need an advocate (or two) in the department to which you're applying. If you sell yourself as an X person, you can get faculty in X behind you; if you sell yourself as a Y person, you can get faculty in Y behind you. However, if you sell yourself as a mix, the X faculty might prefer a pure X and the Y faculty might prefer a pure Y. Of course, this isn't always true: Maryland is basically looking for a combined NLP/ML person this year to compliment their existing strengths. Of course, this doesn't always hold: this is something that you should try to find out from friends at the places to which you're applying.

For the application process itself, my experience here and what I've heard from most (but not all) universities is that interview decisions (who to call in) get made by a topic-specific hiring committee. This means that to get in the door, you have to appeal to the hiring committee, which is typically people in your area, if it's an area-specific call for applications. Typically your application will go to an admin, first, who will filter based on your cover letter to put you in the right basket (if there are multiple open slots) or the waste basket (for instance, if you don't have a PhD). It then goes to the hiring committee. Again, if you have a friend in the department, it's not a bad idea to let them know by email that you've applied after everything has been submitted (including letters) to make sure that you don't end up in the waste bin.

Once your application gets to the hiring committee, the hope is that they've already heard of you. But if they haven't, hopefully they've heard of at least one of your letter writers. When we get applications, I typically first sort by whether I've heard of the applicant, then by the number of letter writers they have that I've heard of, then loosely by the reputation of their university. And I make my way down the list, not always all the way to the bottom. (Okay, I've only done this once, and I think I got about 90% of the way through.)

In my experience, what we've looked for in applications is (a) a good research statement, including where you're going so as to distinguish yourself from your advisor, (b) a not-bad teaching statement (it's hard to get a job at a research university on a great teaching statement, but it's easy to lose an offer on a bad one... my feeling here is just to be concrete and not to pad it with BS -- if you don't have much to say, don't say much), (c) great letters, and (d) an impressive CV. You should expect that the hiring committee will read some of your papers before interviewing you. This means that if you have dozens, you should highlight somewhere (probably the research statement) what are they best ones that they should read. Otherwise they'll choose essentially randomly, and (depending on your publishing style) this could hurt. As always, put your best foot forward and make it easy for the hiring committee to find out what's so great about you.

Anyway, that's basically it. There's lots more at interview stage, but these are my feelings for application stage. I'd be interested to hear if my characterization of the hiring process is vastly different than at other universities; plus, if there are other openings that might be relevant to NLP/ML folks, I'm sure people would be very pleased to seem them in the comments section.

Good luck, all your graduating folks!

We're hiring machine learning/robotics...

Just a quick note because this is a bit off-topic for this blog, but I wanted to let you all know that this year, we're trying to hire a machine learning/robotics person. If you do machine learning that in any way is robotics related, I'd encourage you to apply. (I suppose same holds the other way around, but I probably wouldn't be quite as excited.) The "deadline for full consideration" is listed as Jan 15, which has passed, but if you apply by the end of the month, things would be fine. In the interest of full disclosure, we're also hiring in graphics, systems and sensor networks.