In continuing my search and preparation for a faculty position, today I attended a mini-seminar by LADO faculty. (LADO - liberal arts colleges with diversity officers) Here are some points that were raised during the breakout and panel discussions:
Teaching:
- You will teach both upper-level courses, as well as "service" courses. Service is a good term to describe the low-level / introductory courses, as the faculty are rotating through this service to the department.
- Try to setup the teaching schedule so that 1 day is free solely from research.
- Continue to revise courses so they are fresh and current, but also avoid constantly creating all new courses.
- Valuable to set aside "non-office hours" times, during which the door can be shut.
- Faculty will sit in on courses and additionally interview the students, as part of composing an evaluation of your teaching.
Research:
- Recruiting undergraduates earlier for research to have time to train them, so that they will later be able to contribute.
- You can still collaborate and have broad impact through research with faculty at other more research-focused institutions.
- Grant proposals can also be keyed "RUI" (research at undergraduate institutions)
- Regular funding for sabbatical leaves, first often after the renewal of the 3-year contract. This leave is focused on research and may be held at R1 or other institutions.
- Startup package is present to cover the transition to grant-based funding.
- Research lab costs are significantly lower at these institutions, as funds are not required for grad students, post docs, etc.
- Schools are looking for faculty hires that add diversity to the research available.
Service:
- Service is a component, but is much smaller than teaching and scholarship. So be cautious about accepting invitations to committees, in terms of time commitment. The service time can provide valuable insight to the functioning of the institution, as well as possible collaboration with collegues in other departments.
- You will be chair of your department someday.
Other:
- Many liberal arts institutions are located in small towns.
- Take the time to customize the cover letter. Do you really want and care about this job?
Monday, October 27, 2014
Wednesday, October 15, 2014
Richard Lipton - Knuth Prize (Practice) Talk
Richard J. Lipton is the 2014 winner of the Knuth Prize. His talk today was a summary of his work, which lead to received the prize. The talk proved to be a series of short anecdotes, which are difficult to capture, but I've copied down the highlights, as best as I can.
"Do problems have labels?" For example, simulate a queue as two stacks, is this a theory problem or system problem? At the time, the qualifying exams were split by problem types, so labeling it mattered for which exam contained it. Faculty at Yale were 50/50 split on whether to mix the problem types and instead students would sit for several days of CS questions rather than a theory day, then a systems day, etc.
Finding a division, separator to a planar graph, in root time. T(n) <= C*T(n/2)
In explaining the result to Knuth, while visiting Tarjan, who responded "You've ruined my lunch." As the result destroyed the best known algorithms that were being written, at the time, in Vol. 4.
"Throw away comments are wrong" Many introductions make inaccurate statements like "non-uniform cannot imply uniform". There is the work of Karp-Lipton dealing with non-uniform circuits and the uniform nature of algorithms. The proof was later handed out on tote-bags at CCC 2010.
"Think in High Dimensions" Binary search in high dimensional space, still logarithmic in the number of elements. For example, take a planar graph and split it by the intersections, each slab is linear and can be quickly searched.
"Learn New Tools" Now, one tool is "Probabilistic method" published on June 28, 1974, which shortly thereafter was a Yale seminar. "By an Elementary Calculation" means to Erdos to use Sterling's approximation, which in one case required taking the approximation to 7 places. Before learning this method, had been asked about the problem of Extendible Hashing, and had no idea and put it out of mind. Later asked about it again, and the problem solved easily (or perhaps two days of proofs).
"Guess Right" One problem in solving problems in the community is that we are guessing wrong. "It is really hard to prove false statements." Take the problem of detecting whether a sequence of a_nb_m has n = m? Possible using a multi-pass scan with a probablistic FSM. Can do with one-way (i.e., single pass)?
"Need a Trick" Solving a problem of vector addition, with fixed counters, with adding and subtracting (where cannot subtract from 0). 1 counter is decidable, 2 counters is not. But if there is no test for whether the counter is 0. Proved it takes EXPSPACE-hard. Pair counters, so add is subtract and vice versa.
"My Favorite Two Results" - Proving that a a^-1 = 1, in long sequence (abaaaba^-1...) can be done in LOGSPACE. Do so by replacing the a, b with matrices, then modulo prime. Given the distributed law and applying in any order, prove that it always stops on any expression.
"Future" Old problems, yes. But dream of finding proofs to math problems that use CS theory tricks.
"Do problems have labels?" For example, simulate a queue as two stacks, is this a theory problem or system problem? At the time, the qualifying exams were split by problem types, so labeling it mattered for which exam contained it. Faculty at Yale were 50/50 split on whether to mix the problem types and instead students would sit for several days of CS questions rather than a theory day, then a systems day, etc.
Finding a division, separator to a planar graph, in root time. T(n) <= C*T(n/2)
In explaining the result to Knuth, while visiting Tarjan, who responded "You've ruined my lunch." As the result destroyed the best known algorithms that were being written, at the time, in Vol. 4.
"Throw away comments are wrong" Many introductions make inaccurate statements like "non-uniform cannot imply uniform". There is the work of Karp-Lipton dealing with non-uniform circuits and the uniform nature of algorithms. The proof was later handed out on tote-bags at CCC 2010.
"Think in High Dimensions" Binary search in high dimensional space, still logarithmic in the number of elements. For example, take a planar graph and split it by the intersections, each slab is linear and can be quickly searched.
"Learn New Tools" Now, one tool is "Probabilistic method" published on June 28, 1974, which shortly thereafter was a Yale seminar. "By an Elementary Calculation" means to Erdos to use Sterling's approximation, which in one case required taking the approximation to 7 places. Before learning this method, had been asked about the problem of Extendible Hashing, and had no idea and put it out of mind. Later asked about it again, and the problem solved easily (or perhaps two days of proofs).
"Guess Right" One problem in solving problems in the community is that we are guessing wrong. "It is really hard to prove false statements." Take the problem of detecting whether a sequence of a_nb_m has n = m? Possible using a multi-pass scan with a probablistic FSM. Can do with one-way (i.e., single pass)?
"Need a Trick" Solving a problem of vector addition, with fixed counters, with adding and subtracting (where cannot subtract from 0). 1 counter is decidable, 2 counters is not. But if there is no test for whether the counter is 0. Proved it takes EXPSPACE-hard. Pair counters, so add is subtract and vice versa.
"My Favorite Two Results" - Proving that a a^-1 = 1, in long sequence (abaaaba^-1...) can be done in LOGSPACE. Do so by replacing the a, b with matrices, then modulo prime. Given the distributed law and applying in any order, prove that it always stops on any expression.
"Future" Old problems, yes. But dream of finding proofs to math problems that use CS theory tricks.
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