Showing posts with label jobs. Show all posts
Showing posts with label jobs. Show all posts

Wednesday, February 11, 2015

One Body Problems

It's hiring season, and we've all heard about two-body problems.

But you may not have heard of the one-body problem:
Is the place a single person takes a job in likely to have enough other single people around to facilitate searching for a partner ? 
I was 'spoken for' before I even finished my Ph.D, and never had to deal with this (rather, I had to work with the more traditional (ha!) two-body problem).
 


Tuesday, January 08, 2013

ICERM and Simons postdocs

Two upcoming TCS postdoc deadlines:

ICERM Program on Network Science and Graph Algorithms

This is a program out of Brown organized by Kelner, Klein, Mathieu, Shmoys and Upfal. It sounds quite fascinating if you're doing anything with graph data and spectral analysis. Deadlines for postdoc applications is Jan 14.

Simons special program on the theory of big data. 

As I've mentioned before, the Simons Institute is running a semester long program on the theory of big data. The deadline for applying for postdocs is soon (middle of January)

These two programs are coordinating, and if you're so inclined you might be able to spend one semester at Berkeley and another in Providence. Please let the organizers know if this is something you're interested in.

Monday, October 08, 2012

On why I'm excited about "big data"

I was in Aarhus recently for a MADALGO workshop on large-scale parallel and distributed models, where I did a sequence of lectures on GPU algorithms. I was briefly interviewed by a university reporter for an article, and did a little video on why I think big data/big iron problems are interesting.

At the risk of embarrassing myself even more than I usually do, here's the video. Note that this was recorded at a time of great crisis across the globe, when all hair styling products had mysteriously disappeared for a few days.


Wednesday, October 03, 2012

We're hiring FIVE (count 'em, FIVE) faculty this year.

We had an incredible hiring season two years ago, making seven offers and hiring seven new faculty. And now we're doing it again !

Our department is looking to hire five new faculty (at least four are at the assistant professor level). I'm particularly excited that we're hiring two people in the general area of big data (following up on our data mining and database hires from two years ago).

One slot is in what I'll call "big data meets big performance": I'll have more to say about this shortly, but the challenges of large data analysis are not just about managing the data, but about managing large numbers of machines to crunch this data (MapReduce is perhaps the most well known example of this). We're looking for people who can "speak extreme data and extreme processors" fluently - these could be on the data/systems management side, or on the analysis side, or the modelling side.

Utah has a strong presence in high performance computing (the Supercomputing confererence is happening in Salt Lake, and Mary Hall is the general chair), and we're one of the few places that has a good understanding of both sides of the large data story (i.e machines and bits).

The second slot is in machine learning, with ties to language. Text (and language) provide one of the best large data sources for scalable machine learning, and we're looking for people interested in the challenges of doing ML at scale, especially when dealing with NLP. If you're that person, you'll be coming into a department that has the entire range of data analysis folks from algorithms to analysis to systems to NLP (with many other faculty that are heavy users of ML technology).

Our plan, once we fill these slots, is to make Utah a one-stop shop for large-scale data analysis and visualization - in addition to the above slots, we're also looking to hire in information visualization to complement our strong viz presence.

In addition to the above slots, we are also hiring in computer security and HCI/user interfaces. While I'm equally excited about these positions, I know much less about the areas :). I will point out that we have a big systems group that covers many aspects of security (language security, verification, and network security) already. We've also had strong demand from students and industry for research in HCI, which will complement our info-viz efforts (and even our data mining work)

For more details on how to apply, see our ad. We'll start reviewing applications after Dec 1. Feel free to email me if you have questions about the slots (but don't send me your application material - send them in directly)

Disclaimer: the above views are my own personal views, and don't represent the views of the department or the hiring subcommittees.


Sunday, April 08, 2012

Postdoc Announcement

Piotr Indyk asked me to post this announcement for a postdoc position:

Applications are invited for a Postdoctoral Research Assistant position for the MIT-Shell-Draper Lab research project

"Applications of compressive sensing and sparse structure exploitation in hydrocarbon reservoir exploration and surveillance" 

The goal of the project is to develop novel compressive sensing algorithms for geoscience problems in the area of hydrocarbon field exploration and surveillance. The appointment is initially for one-year, with the possibility of renewal for up to 3 years. The appointment should start either during the summer (the preferred option) or the fall of 2012.

 Duties and Responsibilities: 
  • Provide expertise on and contribute to the development of compressive sensing and sparse recovery algorithms for geoscience applications
  • Help MIT faculty in coordination of research projects, including periodic reporting and documentation as required by the program timeline
  • Frequent travel to Shell facilities in Houston 

Minimum Qualifications
Ph.D. in Computer Science, Electrical Engineering, Mathematics or related disciplines

Preferred Qualifications
  • Expertise in sparse recovery, compressive sensing, streaming/sketching, machine learning and statistical inference algorithms
  • Experience and/or interest in research projects of interdisciplinary nature
  • Programming experience (MATLAB) 

Applications (including CV and three reference letters) should be submitted to https://postdoc.csail.mit.edu/searches/sparsityp-search/ ideally by April 15, 2012. However, applications will be considered until the position is filled.

Wednesday, June 22, 2011

Applying for Jobs: the Job Talk

This is the fifth post in a series on applying for faculty positions. It is written by Jeff Phillips, frequent guest blogger, who will be starting as an Assistant Professor at the University of Utah starting Fall 2011.



The final component of applying for jobs is the job talk. It will usually be about an hour, but may vary so ask. Usually this means you can talk for about 58 minutes, before they want to stop you for questions. But again, its best to confirm this, try to ask your host specifically about this. Also ask about how frequently you should be expected to be interrupted with questions during the talk. Of course, this may vary greatly from talk to even at the same place (as I have seen in my experience). But, from my perspective, many instances where the speaker was delayed for more than 5 minutes due to questions in the talk was the fault of the speaker. This usually occurred by leaving ambiguities in the talk, by failing to answer questions clearly and concisely (this may lead to more questions), and by not taking charge and insisting on taking longer questions off-line.
The most important failure (ambiguities) will hopefully be avoided by taking the steps below.



First, what should you talk about?
  • Talk about your best work!
  • Talk about your work that appeals to a broadest audience and that you can convey the main ideas of most clearly.
  • Talk about the project you are most well-known for, this is probably because its your best received, and likely your actual best work even if you have some "personal'' connection to some other topic.
  • Talk about the work that is most likely to get you hired. This last one can be tricky, but try to ask your host or anyone else you know at the institution what specific type of person they are looking to hire. No one will fit a mold perfectly, but make sure the faculty there don't have to squint too hard to see you in fit in that mold.
If it is the same topic that fits all of these criteria, then you have a much easier task. Otherwise, you may need to compromise on some these. Try not to sacrifice strength of work and clarity of key ideas. If you are not sure which topic is your strongest, ask around.



What should go into talk? Not too much.
Present at most 2 or 3 main ideas. Most papers have one main idea, even if there are several smaller ideas in the paper. The lasting contribution is usually one key insight, (even if it took a lot of hard work and many other technical details to get everything to work). Try to abstract away those technical details, and convey the main new ideas your work added. You can mention that there were difficult technical details, but do not describe them!

So 2-3 main ideas equates to 2-3 papers. Perhaps you have a series of papers that layer on interesting ideas towards a single goal. In this case, you can possibly convey more, but do not try to cram more at the expense of not making clear what the main conceptual contribution is.

It is also helpful to have the talk tell a story, to have a single narrative. But, if you have two pieces of work that are both your strongest works and easiest to express the key contributions, then give the talk in two parts and choose to convey better work than to give a cleaner, but weaker story.

If you are a theoretician, give at most 1 proof. (Unless, with possible exception, you are being hired into a strong theory group and they alone make the hiring decision, then, maybe, give 2 proofs). Most people will get lost in the details. I gave one proof sketch, but "intuitively explained" why several things were true, usually each in one to two sentences. I am guessing for non-theory people, there is an equivalence between number of "proofs" and number of some other technical descriptions. The point is, it might be good to spend 3 minutes at some point showing off your technical prowess, just to try to convince the audience you are an expert in an area - but there can be better ways of doing this than diving so far into the technical details that you somewhat intentionally loose most of the audience.

You should aim to teach the audience something. That is, go in a bit more depth for some general technique in your field that you feel is not well-understood, and would serve the general audience to know. This does not need to be explicitly your work (and often will not be), but you may have extended this work. If you did extend it, the audience will appreciate it much more if they understand the importance of the general version. In this "teaching segment" the goal should be to allow the audience to understand how to operate some heavy machinery (at least in principle). Spend time developing simple examples that clearly demonstrate how it works and its power.
This segment is also important in demonstrating your teaching abilities. If someone leaves your talk comes away feeling they learned something, even if it was not your specific contribution, then they will have a positive impression. I know when I spend an hour in a talk, and don't come away with this impression, I am very disappointed in the speaker.



How should you structure your talk?
Spend the first 10 minutes motivating the entire area you are working in, and then the set of key problems in the area. Start at a very high level, and use well-planned examples to zero in on what are the major hard problems in the area, and why they are the critical remaining component in advancing the sub-area. This should allow you to outline the rest of the talk by just saying which of these problems you solved (and then spending 40 minutes explaining how).
This first 10 minutes of motivation can be modified if you give job talks at several place without changing much of the forth-coming meat of the talk. This may be necessary to paint yourself in a few slightly different roles depending on what each university/lab is looking to hire. Minor changes in the set up, can give the talk a very different flavor, perhaps focusing on different aspects that potential collaborators at each institutions could appreciate as fodder for possible proposals they could write with you.

Then spend about 15-20 minutes each on covering your contribution in 2-3 core problems. Probably don't spend more than this on any one topic, since if you lose some audience members, you can re-captivate them for the next section. And any less than this, you probably will not be emphasizing the contribution enough, and it you don't feel it deserves that much, then your talk might be cleaner if you did not waste the time to mention it.

Within each of these sections, explain the core problem in more detail, explain what other approaches are available and why they do not work. This should lead naturally into what you did. Do not just show results saying that your approach was better, make sure to explain the key idea of why your approach was better. What made you approach succeed when no one had before? If an audience member cannot immediately answer that question, then they may likely come away with the impression that you did not do anything interesting, other than tightening the existing bolts. You can conclude each section by mentioning extensions to this work, either your or others. These extensions are especially useful if they demonstrate how your key idea was integral in advancing the field.

Finally, there is likely other work that is not one of they 2-3 key contributions that you have done. You probably want to talk about it more than you actually should :). I dealt with this in two ways. Given than I had described a set of an important problems in the first 10 minutes with several sub problems, after a couple sub-problems I described my contribution for, I listed on a single page all of the other work I had done in this related sub-area. This allowed me to mention it and also have it in context of the field I was overviewing.
The other way was just to have 1 or 2 slides are the very end of the talk listing other work I had done. Its good to show you are broad, and that you have completed a lot of work. But its also easy to see this from glancing at your CV. So in these 1-2 slides attempt to cast each other project you did not talk about in relative comparison to the work you did talk about. If you mentioned 2 projects, and you had 4 other ones of similar proportion, try to convey this. This is more informative than CV paper-counting.

Conclude your talk with your vision for the next 5-10 years worth of research. I felt it best not to focus on specific problems, but on how the work I had done would have an impact down the road. Anyone can do work in a certain area or solve specific problems, but if you convince the audience that your work will be important for a lot of important future work, then not only did you have the foresight to produce that work, but you are well-positioned to continue to contribute in the field.



Finally, practice, practice, practice!!! I think I practiced my talk at least 50 times. Thats 50 hours of just speaking. When I mentioned 58 minutes to speak earlier, I meant more-or-less exactly 58 minutes (plus or minus 15 seconds). If you practice enough, you will know exactly how long the talk takes as a whole, and how long each sub-section takes. If you get a lot of questions in some early part and lose 3 minutes, you will know where you can make it up in a later part.

Also, practicing it will help you realize what is explained well and what is not. If you repeatedly find yourself explaining a slide and wishing you had a figure to help explain that, then add the figure. If there is another slide that has a figure that you don't really need, then remove it.

I only had the opportunity to practice in front of an audience (other than at actual interviews) twice. So, I spent a lot of time sitting in a room by myself talking to myself :).

So, the key take-aways are: (1) motivate the field to convince the audience your problems are important, (2) make sure you convey 2 or 3 main conceptual contributions, focusing on key new ideas, (3) teach the audience something, (4) demonstrate vision for the future, and (5) if you practice enough and keep these in mind, you will definitely give an excellent talk.

Wednesday, June 15, 2011

Applying for Jobs: On-Site Interviews

This is the fourth post in a series on applying for faculty positions. It is written by Jeff Phillips, frequent guest blogger, who will be starting as an Assistant Professor at the University of Utah starting Fall 2011.



Today's post is about what do do once you actually get a job interview. I'll try to cover everything except the job talk which will come in the final post.

You will usually be assigned a host. Talk to this person and try to get a feel for what the department is looking for. Perhaps the AI person is retiring and the department is happy to hire an Algorthims person as long as you can also teach AI. Or you would be the only theory person in the department and some of the other faculty are nervous of this, so the more you can talk about real world applications the better. These are very important things to find out.

And if you know other people in the department, by all means, ask them as well. If you get hired, you will need an advocate to make your case. Contact who you think might be an advocate for you. Don't be shy!

Try to figure out who the big shots are in the department. These people may be more senior or outspoken, bring in more money, and most importantly can potentially have way more influence than other people. If you can connect with these people, all the better. Sometimes hiring is done entirely within an area, so then the big shot is relative to the area.

Starting a week to a few days before the interview, try to get a schedule of your visit, even if it is only a draft. Research everyone on your schedule, know about their research areas and what classes they teach. All of this can usually be found on their webpage. Also try to read at least one of their recent papers that has the best probability of have some intersection with your research. And prepare several questions or topics for potential discussion.

Several people may be on your schedule who do research that is not really similar to yours. These people may be on the hiring committee, and should not be ignored. Try to make connection, even if it's not entirely about research. Like if you went to a common school , or know common people.

There is a good chance for last minute changes to your schedule, so research others in the department as well even if they are not on your schedule.

Also prepare answers to he same sort of questions as for phone interviews. If you suggest that you would teach a class, make sure you have many of those details sketched, because you may get asked specific questions about what you will cover.



On the actual visit I always carried a print-out of all of my notes, but never got a chance to look at it. So you'll have to memorize most of he information on there.

It is important to try to make positive connections with as many faculty as you can. Be friendly, outgoing and smile. Make eye contact. Be very excited about what your research. And obviously, don't say anything sexist or racist. Seriously, save the dirty jokes for later.




I've heard you should follow up with a short email with everyone you met, but I did not do this. I only sent something if it was meaningful. Like specific follow-up to a problem we discussed, or replying to a specific question. Usually about 3-5 per visit.


Tuesday, June 07, 2011

Applying for Jobs : Phone Interviews

This is the third post in a series on applying for faculty positions. It is written by Jeff Phillips, frequent guest blogger, who will be starting as an Assistant Professor at the University of Utah (yay!) starting Fall 2011.



A part of faculty interviews I had not heard or thought as much about was the phone interview. Not sure this was my strength in the interview process, since more places I had phone interviews did not follow-up with on-site interviews, than did. So if you have any different experiences, please post in the comments.

Some places do not have phone interviews, as some of my on-site interviews did not first have a phone interview. From my perspective, the places that did have phone interviews were places that may have wanted to confirm I was actually interested in coming. There were always several questions about why I was interested in that particular location/university.

Anyways, I'll try and provide some advice for performing well on phone interviews, even if I did not necessarily follow all of my advice.

First, prepare for these as if they were an on-site interview. Practice answering questions with someone over the phone (or in a room without eye-contact). You need to keep answers relatively short and to the point. Its harder to listen to a long answer over the phone. And its harder to take hints if you are giving too long or too short of an answer. Its probably more important here than in an on-site interview that you are well-prepared for questions, since you can't, say, move to a white board to explain something in more detail with a picture.

Try to figure out who will be on the other side of the interview a head of time. I've had one-on-one interviews as well as group interviews. The entire hiring committee was on the other side. Although usually in this case, one person asked most of the questions, but others would add follow-up questions. It could be a bit disorienting. When it was just one person, I usually tried to have their webpage up on my computer so I had a picture of them.

And, research who your interviews are, what their research areas are, and what classes they teach. If they bring up an topic, make sure you don't disrespect their research area, and you can try to positively relate to it if its relevant. If they realize you put in this effort, it will definitely help show you are serious about that university, which, I believe is a key aspect of why they are calling you.

Most importantly, make a list of potential questions and prepare and practice answers for them. I tried writing down answers, but this was not necessarily good on the interview since I really felt like I was just reading answers at some point. I'd rather suggest writing them down just to organize your ideas, but don't necessarily have them in front of you during the interviews. Bullet points might be ok.

Here are a list of questions similar to those I had:
- why do you want to go to UofX?
- why the location of UofX is attractive?
- who will you collaborate with? (try and answer with actual names, in the department)
- how will you fit in the department?
- what will your first proposal be about? (here they want to get a feeling that you have thought about proposals, name specific funding agencies and calls if you can. Don't be shy to mention any experience you have writing proposals even if you are not asked.)
- what you will teach? (try not to duplicate existing classes, especially not special topics ones)
- what is your research areas?/describe you research. (You may choose a topic so that is easy to describe over the phone.)
- Do you have any questions? (This one always gets asked. Sometimes you get the option to ask this at the beginning or wait til the end. I recommend waiting, since it allows the interview to get underway at first and you can get a sense of your interviewers before you ask.)

For faculty interviews, you probably won't get any technical questions (although you might - I did for research lab interviews).

And finally, you will probably have no idea how well it went after it is over. Don't worry this is normal, but quite frustrating. And you may not hear back for a couple weeks or more, so hang in there.

Applying for Jobs : Sending out Applications

This is the second post in a series on applying for faculty positions. It is written by Jeff Phillips, frequent guest blogger, who will be starting as an Assistant Professor at the University of Utah (yay!) starting Fall 2011.



I found actually applying for faculty jobs takes a lot of time. Maybe I spent too much time and others were successful with a less time-consuming approach; if so please add your perspective in the comments.

The first step is to find which jobs to apply for. I basically completely relied on the CRA jobs website to find out about job openings. Often I found that job listings appeared on their within a day or so of the listing becoming available on the school's website.
Comically, CRA also posts the same ads in a written newsletter which I get every couple months. The print edition appears several months later, often after the deadline has passed.

Some jobs will not appear on the CRA website. Some top schools don't need to advertise, so for those you need to either look for some ambiguous statement of faculty recruiting on the school's website, or better ask someone you know at that school (or have your advisor ask).

In fact, it is very important to have an advocate within any school you hope to get hired. So, as you are seeing friends or colleagues at conferences ask them "are you hiring next/this year?" For one, it is often a great conversations starter, and two, you can start implanting the thought in their head that you would be an excellent person to hire. I've heard that the head of the hiring committee can craft the description of the job posting to aim towards a particular type of candidate, or even a single particular candidate they are aiming for. Now is the time to approach you colleagues at universities you might want to apply and subtly try to get them to build an opening designed for you!



OK, now that you have found (or even crafted) the opening you are applying for, what is left to do? You already have your research statement, your teaching statement, and letters lined up that you have been working on-and-off all summer on.

The most customizable item is the cover letter. I've been given advice that you don't even need to write a cover letter unless it is required (presumably from people who when on the committee never even looked at them). While this may often be true, I felt it was worth trying to make a point of why this university it right for you.

Some middle tier university get many applicants with somewhat comparable resumes. How can you associate yourself with that university so they think if they made you an offer you would actually come? Have you lived nearby and liked the area? Do you have family nearby? Is there a particular program that the university is strong in that would be a great fit for you.

Also what I spent the most time on, was describing who I might collaborate with, within the department. Don't spend too much time on people outside the department since they usually have no bearing in the hiring decision. But if you have a lot of similar interests with someone on the hiring committee, definitely point those out. This usually took me 45-60 minutes per application, because not only did I want to find someone, I did not want to leave someone out. Perhaps, I could have not spent this time, but I felt it made a difference.

One thing I did not do much of, but could have done, is personalize the type of classes I would teach as described in my teaching statement. If someone, especially someone with similar background to you, already teaches a class very similar to a "new" one you propose, then many people outside that area would interpret that as you duplicating that person, and they would rather hire someone who could provide more breadth to the department. Rather, what I should have done is to try to identify which types of classes were missing from the university and adapt my teaching statement accordingly.

I've had advice saying I should prepare a few classes I would develop in my statement, and then choose which one to submit based on what the need was in the department.


Finally, the most important advice is to not rush the application process. I tried to do 1-2 applications every night for about 3 weeks (I submitted a lot of applications). This had two reasons, first it took me about 1 hour per application (some customization, but sometimes because of stupid forms). Second, if you do too many in a row, you get burnt out and start cutting corners.
Treat every application as if it is your top choice. Every time I applied, I convinced myself that this was a great place for me, and got in that mind set. For a few places where I just could not convince myself of that, I ended up not applying. I figured it wasn't worth anyone's time for me to submit a half-hearted application.




One final note. Although I intended for this series to be mainly about applying for faculty jobs, most of the advice carries over for research labs. I knew I wanted to apply for faculty positions, but I also applied to some research lab positions, and as it turned out, I almost went to one instead of accepting the Utah position. It seems each lab is somewhat different, and you might be pleasantly surprised if you get a chance to visit.

Most labs have some sort of hiring every year. But you generally need to know someone (or your advisor/mentor does) to get you foot in the door. Internships are a great way to meet these people and get the proper perspective. So, again ask colleagues at labs about hiring, and go through them to apply.

Saturday, June 04, 2011

Applying for Jobs: Application Material

This post is written by Jeff Phillips, frequent guest blogger, who will be starting as an Assistant Professor at the University of Utah (yay!) starting Fall 2011. Content edited lightly for formatting only.



Several people have recently asked me about applying for jobs, so I thought I would write a post (or a series of posts) about it. Other posts will be on:
  • Sending out Applications
  • Phone Interviews
  • On-Site Interviews
  • Job Talks
You may be saying, isn't this the wrong time to give advice about applying for jobs. My first piece of advice is: Now is the time to start planning your job search.

If you are planning to apply next year, then put together an application now. You will need a research statement, a teaching statement, a CV, and a list of 4-5 people to write letters.

The Research Statement should accomplish three things:
  1. Show you have breadth to your research.
  2. Show you have depth to your research.
  3. Show your research has potential to get funded in the immediate and long term future.
I tried to structure mine as several subareas I worked on describing one project in each area in a bit more depth (2-3 sentences worth). Then I had a section at the end outlining some future directions.

I felt it was also important to try to shape this in a single research story. This meant I left out some elements of my work. Don't try to fit everything in if it does not fit the best cohesive story. No one will have time to read through all the details of what you did, and if they did they can find it on your CV or webpage.

Also, this needs to be written at a level that is accessible to a general person in computer science - not an expert in your area. Too much technical detail will not help, the committee does not have time to try to understand technical details. Describe the motivation and the key technical insights you added to the field.

The Teaching Statement is secondary. What I have heard is it will not affect how your overall application is judged at many research institutions. And that their best indication of how good a teacher is will depend on how well you execute your job talk.

The best advice I've been given on the teaching statement is that it should support your research statement. So, discuss how you will teach about your own contributions to the field. Describe a new class or two you will teach that builds on what you talk about in your research statement. Think of this as a committee member might spend an extra 2-3 minutes reading this document. So don't waste that time on what classes you have taught, rather, use this as another opportunity to demonstrate the importance and excitement about your research direction.

Your CV should list everything you can think of. There is rarely a space limitation on this document, so go wild. List all papers, talks, awards of any kind, services. But make sure the first page highlights the most important things you want the committee to notice. And if you want them to notice it, then by all means make it bold. And of course, nice use lists, structures, and formatting so they can easily find what they are looking for. They may spend 1-2 minutes (or less) on this document, so make sure its very easy to navigate.

I also numbered my papers so I could easily refer to them in my research statement without repeating that information. Think of this all as a single document, and don't repeat information.

You will need 4-5 Letters of Reference, and these can (ed: and usually are) be the most important part of your application. Most places ask for 3 letters, and some 4. But if they allow it, as long as each letter is strong and tells a different story about you, extra references don't hurt. Also, I found depending on the job description I sometimes added a 5th letter writer who might have more connections at that particular place. You don't need to ask these people now, but you should start thinking about who would best represent you.

One person will almost always be your advisor, unless you have a unique situation. The best letter writers, I've been told, are well-respected people in your field, who you have not written papers with, and who are not at your university. But only ask for letters from people who can say meaningful things about you.



OK, so why should you be doing all of this now? Wouldn't it be more up-to-date if you prepared this material right before you applied? Yes! But getting these documents right will take many iterations. If they are done ahead of time, you can ask your very busy advisor for feedback and be ok if it takes her/him 1-2 months. If you have other friends who have recently been on the market, ask them too; and ask them for their research documents for examples. Ask professors in your department for advice; they are usually happy to give advice and it will always be different.

You don't need to ask for letter writers now, but it might be good to sit down with your advisor with an extended possible list, and plan together who would be good to ask. If there is some communication or project with someone well-known in your area who might be a good letter writer, you still have half a year to make a good impression. If you have them in mind as a possible letter writer, then make an effort to respond promptly to them when you have interactions, and try to say hi and talk to them when you see them at conferences.

When you have written your research statement now, look for holes in it. What is one more project you can complete or make significant progress on that would most enhance the statement ? I would argue that one project that fills out your research story and introduces new ideas or connects to a nice hot area is much better than two papers submitted to a journal, or an extension to a project that makes your thesis more complete but does not introduce a new idea to the field. Save this more incremental work for when you are stressed out waiting to hear back on interviews (or for future students to help them get into your area :) ).

At this stage last year I basically planned out several projects I would work on with aim of completing them in time so I could talk about this in my application. I had not necessarily published them when I applied, but I had the results. Between this time last year and when I submitted my applications, any project that was not directly influencing the main story was made secondary.


One final thing to keep in mind is that application deadlines vary greatly. Some will be due in September or October. Some not until February. A few slots will not open until March or even April. So, if you are prepared early, you will make some early deadlines that others will not.

Saturday, February 26, 2011

Phone interviews ?

Phone interviews are common in the industrial hiring scene. As a candidate, you go through a phone interview (or even two) and if you make the cut, you fly out for an actual interview.

I'm seeing phone interviews become more common in the academic world. You get a phone interview with some member of the recruiting committee, and the actual interview follows if you make the cut.

Has this always been like this (and am I just misremembering?) or is it a new trend ? Phone interviews can make a lot of sense if you want to weed out candidates who might look promising on paper, and it's a clear cost-saver (and time saver), but I haven't seen them be so common in academic settings. Maybe it's because there are more people chasing each slot and so these filters are more necessary now ?

Wednesday, February 02, 2011

IMA Special Year on the mathematics of information

Dana Randall mentioned at SODA  that the IMA (the Institute for Mathematics and its Applications) is looking for increased participation from folks in computer science.

Anna Gilbert at the University of Michigan (and former AT&T colleague!) is one of the organizers of the current 'special year' at the IMA, and it's on a topic that I think many theoryCS folks will be interested in: the mathematics of information.
They're taking applications for postdocs (speaking of which) up until February 4 (two days from now!). So get those applications in.

And what's the special year about ? In Anna's words (edited for formatting):

The Mathematics of Information

During the academic year 2011-2012, the annual program at the Institute for Mathematics and its Applications (IMA) at the University of Minnesota will be in the Mathematics of Information.  Information, broadly defined, plays an ever increasingly large role in our scientific and technological endeavors, as well as our daily lives. Collectively, we search the web over billions of times per day, we keep our medical records in digital repositories, we share videos and photos over the web, and we listen to music on MP3 players. Our ability to collect, store, and generate vast quantities of data far outstrips our ability to analyze, process, and understand these data. Many scientific, engineering, and medical applications depend on our ability to handle enormous amounts of complex information. Network engineering involves massive datasets at high speeds, medical imaging generates large data with intricate geometric relationships, and astronomical observations include data at different wavelengths or spectral bands.  Our current technology and scientific tools for information lag far behind our ability to collect enormous amounts of data, our need to analyze that data as efficiently as possible, and, finally, our ability to use that analysis to make sound, timely decisions. 

The special year will include seven workshops with a thematic focus on the mathematics of information and will include topics in mathematics, algorithms, theoretical computer science, machine learning, network analysis, and applications in biology, include medical informatics and group testing for high throughput screening.  Each workshop is designed to be truly interdisciplinary, involving researchers from mathematical sciences, computer sciences, engineering, and other fields.  Interspersed will be Hot Topics workshops, IMA public lectures, and tutorial and/or short courses.  Faculty, graduate students and postdoctoral fellows are invited to participate as long-term visitors, New Direction Visiting Professors, or postdoctoral fellows (either at the IMA or jointly with industry).

You can find more information about the individual workshops at the annual program webpage.



9/26-30/11    Workshop: High Dimensional Phenomena

10/24-28/11    Workshop: Large Graphs: Modeling, Algorithms and Applications
11/14-18/11    Workshop: Large Data Sets in Medical Informatics

2/13-17/12    Workshop: Group Testing Designs, Algorithms, and Applications to Biology

2/27-3/2/12    Workshop: Network Links: Connecting Social, Communication and Biological Network Analysis

3/26-30/12    Workshop: Machine Learning: Theory and Computation
5/7-11/12    Workshop: User-Centered Modeling


Postdoctoral Fellows

Postdoctoral Fellows applications deadline was January 7, 2011 but applications will be considered until February 4, 2011.

These IMA Postdoctoral Fellowships run one to two years, at the option of the holder, starting August 31, 2011. In the second year of the appointment there are a variety of options to enhance career development, including continued work on the fellow's established research program, participation in the 2012-2013 academic year program, teaching, and working on an industrial project. Postdoctoral fellows receive a salary of $55,000 annually, and a travel allowance.

There is also an option for Industrial Postdoctoral Fellows.  In the second year of the appointment, Fellows can work on a project at an industrial partner. 

Visiting the IMA

You can contact the IMA if you would like to visit for a long period of time during the year or come for a short visit, especially associated to a workshop.  There's more information on general visits and short term visits.

There are sources of funding available for both types of visits and the IMA staff are excellent at making such visits possible.

Monday, October 04, 2010

We're hiring !

The School of Computing is looking for three ! count 'em ! THREE ! tenure-track faculty this year, in a broad search with interests in:
algorithms, concurrent software, data bases, data mining, formal verification, large data analysis, machine learning, performance verification, parallel systems, robotics, and theory.
We're looking for interdisciplinary folks with interests in possily more than one of the above, and there are nominally three "areas of interest" that we are looking in: parallel computing, robotics and big data.

For theory folks, probably the most relevant of the three areas of interest is the big data search, especially if you're interested in data mining/machine learning/statistics and other forms of data analysis. But if you have strengths in any of the other two areas, then make sure to highlight that.

Email me if you have any questions about this. I'm very excited about growing our large-data program by getting strong algorithms folks. rec

Wednesday, February 18, 2009

Postdoc opportunity

Kirk Pruhs writes in with another postdoc position. There's no immediate deadline for applications, but the subject of the postdoc relates to the previously mentioned NSF workshop on power management, now (re)rescheduled for Apr 9-10:

I want to investigate algorithmic issues for optimization problems related to power management. [..]

But I am looking to broaden the range of power management problems that I work on. If you are at all interested, I encourage you to attend the NSF Workshop on the Science of Power Management that I am organizing in DC on April 9-10. The workshop participants will consist of leaders in the practice and science of power management, and the purpose of the workshop is to provoke discussion among experts, identify key research directions, and report key findings to NSF. I have funds to support travel to the workshop. [..]

The research will involve searching for algorithmically interesting problems in this area, and solving these problems. It is certainly not necessary for you have any research experience related to power management. What is necessary is that you [are] the type of person that likes to expand their interests into new, exciting, areas of research.

Thursday, January 17, 2008

A Post-Doc opening

I'll post this on the usual forums shortly, but thought I'd place it here since SODA is coming up.
I'm looking to hire a post-doctoral researcher to work with me at the School of Computing. The position is initially for one year, with the possibility of extension for another year based on mutual consent. Applicants must have expertise in algorithms and computational geometry, and preferably should have experience with high-dimensional geometry, approximations, and large data algorithms (external memory/streaming/etc). Some familiarity with differential geometry is a definite plus.

For more on my research, visit my webpage. To apply, please send me a CV, a statement, and three letters of reference. Feel free to contact me if you have questions about the position.
To add to the above: if you think you might be interested, and will be at SODA, drop me a note and we'll try to meet up.

Wednesday, December 05, 2007

Tenure-track position in geometric computation at McGill

Contact McGill Geometry for more details. Here's the summary:
The School of Computer Science at McGill University invites applications for one tenure-track position at the assistant professor level, to begin August 1, 2008, in the general area of geometric computation.

The successful candidate must have a strong theoretical foundation and should be active in research on geometric problems and their applications.

Complete pdf format applications, including a curriculum vitae, a list of publications with copies of one or two sample reprints, a research statement as well as a teaching statement, and the names and e-mail addresses of three references should be sent to [email protected].

Applications will be reviewed as soon as they are received. No applications will be accepted after January 15, 2008.

The School of Computer Science offers a collegial environment with opportunities for interaction with world class researchers in areas including (but not limited to): computational geometry, discrete mathematics, mobile robotics, computer vision , computer graphics, bioinformatics, cryptography and quantum information, reasoning and learning, and scientific computing.

For further information on the School, see: http://www.cs.mcgill.ca.
Deadline is Jan 15, 2008.

Wednesday, May 02, 2007

MAD about ALGOs

The new BRICS Center for Massive Data Algorithmics (MADALGO) is kicking off with a summer school on data streams. It's a 4-day affair between Aug 20-23, in Aarhus, Denmark, and I am told on good authority that along with learning the ins and outs of stream algorithms, you will also take a mandatory course on how to open one beer bottle with another one.

[Side note: you might ask a Danish person, "What do I do if I have only one beer bottle?". Danish Person: < long silence >]

The set of topics are just what you'd expect for a data stream course:
  • Algorithms for metric and geometric data streams
  • Randomized sketching and compressed sensing
  • Histograms, norms and other statistics of data streams
  • Algorithms for ordered data
  • Lower bounds and communication complexity
Registration is free, and accomodation has been blocked at fairly congenial rates. Especially if you're a grad student and have the wherewithal to go, this would be a great opportunity. The school is open to all researchers. Deadline for registration is June 1.

And when you're done streaming, you can go to Legoland, or experience the rather nonstandard (and NSFW) techniques the Danes employ to slow traffic down (NSFW).

Wednesday, March 21, 2007

Job announcements

For people who don't subscribe to compgeom-announce:

Wednesday, February 14, 2007

New Research Center in Massive Data Algorithmics

Lars Arge, crown prince of massive data set algorithms, informs me that MADALGO, a new research center devoted to massive data algorithmics, is now up and running.
Several Postdoctoral positions at the level of Research Assistant Professor of Computer Science are available. Initially, the positions are for one year, but they can be extended by mutual consent. Applications are welcomed from researchers with clearly demonstrated experience and skills in the design and analysis of algorithms and data structures. Applicants with experience with I/O-efficient, cache-oblivious or streaming algorithms, as well as with implementation of such algorithms (algorithm engineering experience), will be preferred. The responsibilities of the candidates include work on algorithms for massive dataset problems in collaboration with center researchers, along with modest teaching responsibilities.
It's a great opportunity if you're looking for somewhere to do a postdoc, and like mucking around with lots of data. Massive data problems have added a profound new dimension to algorithms research, and this center will really help push research in this area forward. There are also Ph.D student positions available.

Thursday, January 18, 2007

Jobs at McGill

'Tis the season.

McGill University is looking to hire in geometric computing and bioinformatics. I can think of at least three reasons for any new Ph.D to apply:

* It's Canada ! Everyone gets funded by the government ! Need I say more ?
* It's in Montreal: where else can you get the feeling you're in a strange dream where you're in Paris but everyone speaks English ?
* You can "do research" in Barbados whenever you like, and definitely in the winter.

and most importantly,
* they have a job opening for people who do geometry for a living. How civilized is that ?

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