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[SIPTA] Vacancies at Utrecht University
by Cassio P. de Campos Dec. 30, 2018

Dec. 30, 2018

6 Assistant Professors in Information and Computing Sciences (Tenure Track 0.8 - 1.0 FTE) https://www.uu.nl/en/organisation/working-at-utrecht-university/jobs Job description Due to our successful teaching programmes and our ambitions in research, the Department of Information and Computing Sciences is expanding. We are therefore actively searching for six motivated, ambitious Assistant Professors in Information and Computing Sciences. Please note that positions offered will vary, depending on experience and expertise. You have a background in Computing and Information Sciences, preferably in the areas of Information Science, Artificial Intelligence, Data Science, Algorithms, Software, Computer Science Education and Process Management and Analytics. Excellent candidates with other areas of expertise related to our current research groups and teaching programmes are also invited to apply. You have proven ambition and talent for research. As teaching is an important and satisfying part of our work, we are searching for people with a demonstrable motivation to teach. The Department is expanding and provides a dynamic work environment. If you are excited to actively participate in shaping the department, you are very welcome to apply. One PhD candidate will be funded for you by the Department in order to start up your research. Qualifications We are looking for 6 Assistant Professors. Ideally your eligibility is exemplified by Research: PhD in Computer Science, Information Science or another relevant discipline; international publications in leading conferences and journals; experience with or good prospects for acquiring external research funds; vision on future research directions in own area of expertise; experience with or readiness to supervise PhD projects; active role in international scientific communities. Teaching: experience with and enthusiasm for teaching and student supervision; ability to teach in departmental BSc and MSc programmes; well-developed didactic skills; excellent command of the English language; experience with or willingness to use innovative teaching methods and (e-learning) technologies; vision on teaching and your own contribution to teaching. Please note that we are also interested in candidates with a focus on teaching. Leadership: play an active and cooperative role in the department and the university; willingness to organize scientific events, such as research seminars or teaching seminars; willingness to partake in departmental committees. The department finds gender balance specifically and diversity in a broader sense very important. In recent procedures we attracted a significant number of women (five out of 10 positions). We are very keen on appointing more female scientists and therefore strongly encourage qualified women to apply. Publication track record, teaching record, and acquired research funds will be weighed against the number of years of academic experience, also taking into account parental leave or a part-time work schedule. Offer We offer a position of 0.8 - 1.0 FTE. The gross salary - depending on previous qualifications and experience - ranges between €3,255 and €5,656 (scale 10/12 according to the Collective Labour Agreement Dutch Universities) gross per month for a full-time employment. Salaries are supplemented with a holiday bonus of 8 % and a year-end bonus of 8.3 % per year. We offer a pension scheme, (partly paid) parental leave, collective insurance schemes and flexible employment conditions (multiple choice model). Facilities for sports and child care are available on our campus, which is only 15 minutes away from the historical city center of Utrecht. More information is available at: working at Utrecht University. We offer you the possibility to develop towards a Basic Teaching Qualification, supported with educational development programs offered by the University. We also offer candidates the possibility to travel to conferences. We offer you the possibility to develop towards a Basic Teaching Qualification, supported with educational development programmes offered by the University. We also offer candidates the possibility to travel to conferences. About the organization A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University, colleagues from various disciplines collaborate intensively towards major societal themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Sustainability. The city of Utrecht is one of the oldest cities in the Netherlands, with a charming old center and an internationally oriented culture that is strongly influenced by its century-old university. Utrecht city has been consistently ranked as one of the most livable cities in the Netherlands. The Faculty of Science consists of six Departments: Biology, Pharmaceutical Sciences, Information and Computing Sciences, Physics and Astronomy, Chemistry and Mathematics. The Faculty is home to 5,900 students and nearly 1,600 staff and is internationally renowned for the quality of its research. The Faculty's academic programmes reflect developments in today's society. The Department of Information and Computing Sciences is nationally and internationally renowned for its research in Computing Science and Information Science. Current research groups are Algorithmic Data Analysis, Algorithms and Complexity, Decision Support Systems, Intelligent Systems, Simulation of Complex Systems, Multimedia, Human-Centered Computing, Geometric Computing, Process Management and Analytics, Organization and Information, Natural Language Processing, Intelligent Systems, Software Technology and Software Technology of Learning and Teaching. Relevant areas of interdisciplinary research include Game Research, Foundations of Complex Systems, Applied Data Science, Artificial Intelligence and Integrative Bioinformatics. The Department has, among others, close collaborations with the University Medical Center, the Departments of Physics and Mathematics, and the Faculties of Humanities and Geosciences. The Department offers Bachelor programmes in Computer Science and Information Science, and four English Research Master programmes in Artificial Intelligence, Business Informatics, Computing Science, and Game and Media Technology. The Department is developing Master programmes in Data Science and Interaction Technology. High enrolment figures and good student ratings make the education very successful. The Department currently comprises 15 full-time Chairs and 105 other scientific staff, including Postdocs and PhD candidates. Additional information Would you like additional information about the vacancy? This can be obtained from Prof. van Kreveld, Research Director, via M.J.vanKreveld(a)uu.nl, or from Marloes Reichardt-Buijs, HR Officer for the Department, via M.S.Reichardt-Buijs(a)uu.nl. Apply To apply, please use the button below. Please attach a letter of motivation, curriculum vitae and the (e-mail) addresses of two references. If you prefer a part-time appointment, you are also invited to apply, preferably stating the desired part-time ratio. The application deadline is 14/02/2019

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[SIPTA] AlCoB 2019: 3rd call for papers
by IRDTA Dec. 24, 2018

Dec. 24, 2018

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[SIPTA] Robotic 2019: early registration December 31st
by IRDTA Dec. 18, 2018

Dec. 18, 2018

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[SIPTA] publish or perish
by Marco Zaffalon Dec. 18, 2018

Dec. 18, 2018

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[SIPTA] BigDat 2019: regular registration January 4
by IRDTA Dec. 11, 2018

Dec. 11, 2018

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[SIPTA] AlCoB 2019: 2nd call for papers
by IRDTA Dec. 4, 2018

Dec. 4, 2018

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[SIPTA] WPMSIIP 2019
by COOLEN Nov. 21, 2018

Nov. 21, 2018

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[SIPTA] Fw: IFSA-NAFIPS 2019 Second Call for papers
by Kreinovich Nov. 21, 2018

Nov. 21, 2018

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[SIPTA] BigDat 2019: early registration December 8
by IRDTA Nov. 20, 2018

Nov. 20, 2018

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Re: [SIPTA] Fwd: Are there imprecise analogues of pseudo-random number generators?
by Marco Cattaneo Nov. 17, 2018

Nov. 17, 2018

Dear all, I can only recommend the paper by Gert and Jasper, which includes several deep results about infinite sequences of 0's and 1's. However, as far as I understand, Marshall is interested in finite sequences of 0's and 1's that are generally accepted as "random", like the ones generated by PRNGs. Unfortunately, I do not know of any non-artificial way of generating such sequences for imprecise probabilities. Since iid sequences of 0's and 1's have relative frequencies that converge due to the law of large numbers, sequences for which the relative frequencies do not converge can be artificially obtained by dropping one (or both) of the two i's in iid. For instance, a sequence with relative frequency of 1's tending to oscillate between 0.6 and 0.8 can be obtained by keeping independence but varying the probability of 1's according to the following sequence: once 0.6, two times 0.9, six times 0.5, 18 times 0.9, 54 times 0.5, 162 times 0.9, and so on (alternating between 0.5 and 0.9 with block lengths increasing by threefold each time). By adding some randomness to the sequence of probabilities, this could be made less artificial, but I do not know of any work in which this kind of ideas is explicitly developed. Best wishes, Marco -----Original Message----- From: SIPTA <sipta-bounces(a)idsia.ch> On Behalf Of Gert De Cooman Sent: Tuesday, November 13, 2018 7:04 PM To: Dr. Alessandro Antonucci <alessandro(a)idsia.ch> Cc: sipta(a)idsia.ch Subject: Re: [SIPTA] Fwd: Are there imprecise analogues of pseudo-random number generators? My reply to Alessandro, building on my previous message : Precise randomness is more than convergence of the sample mean for the sequence – which is what you use in your argument – it implies also convergence to the same limit of the sample mean for any (computably selected) subsequence. (This is the notion of computable stochasticity, which is still weaker than randomness, and therefore implied by it). It is easy to see that if the extreme points are visited in a computable fashion, we can computably select subsequences whose sample mean will converge to any of the extreme points. Or arbitrarily close to any convex mixture of them. So the sequence will then not be precisely random, contrary to what you suggest. Computable randomness (in the precise case) of a sequence is the stronger property that unless you use the exact precise probability as your model for betting on the sequence of digits, you can be made to lose an unbounded amount of money by someone who bets against you using some computable strategy. It is this (martingale-theoretic) characterisation of (computable) randomness that we generalise to the imprecise case in our paper. Every good wish, Gert Prof. Gert de Cooman Universiteit Gent (ELIS–IDLab) — Durham University (Department of Mathematical Sciences) Technologiepark - Zwijnaarde 914, 9052 Zwijnaarde, Belgium t: +3292645653 — iMessage: +32496832628 e: gert.decooman(a)UGent.be w: users.ugent.be/~gdcooma > Op 13 nov. 2018, om 16:33 heeft Alessandro Antonucci <alessandro(a)idsia.ch> het volgende geschreven: > > Dear Marshall, > > For an imprecise subjectivist “the imprecision is in the eye of the > learner”. A non-stationary RNG can jump from one sampling distribution > to another but, again, this is done according to another > (second-order) distribution. The sample will be indistinguishable from > another one sampled from the marginal of that hierarchical model. The > imprecision level is basically a parameter of your learning algorithm > (e.g., s for the IDM, alpha for likelihood-based approachs), but not > something you might learn from your data. > > These are my two cents. > > Bests, > Alessandro > _________________________________ > > Alessandro Antonucci > IDSIA > Dalle Molle Institute > for Artificial Intelligence > Via Cantonale (Galleria 2) > CH-6928, Manno-Lugano, CH > > mail: alessandro(a)idsia.ch > skype: alessandro.antonucci > tel: +41 916108515 > web: www.idsia.ch/~alessandro > _________________________________ > > > ---------- Forwarded message --------- > From: Michael Smithson <Michael.Smithson(a)anu.edu.au> > Date: mar 13 nov 2018 alle ore 14:55 > Subject: Re: [SIPTA] Are there imprecise analogues of pseudo-random > number generators? > To: <alessandro.antonucci(a)gmail.com> > > > Hi Marshall, > > It isn't clear to me what you want the long-run state to be. Do you > want p(1) to settle down to having, say, a uniform distribution on > [.6,.8]? Or for the relative frequency of 1's to end up strictly > confined between .6 and .8? Or are you thinking of having p(1) fixed > at .7 and some other random variable controlling the interval width > around .7 that eventually settles on a width of .2? Or ... ? > > Kind regards, > > --Mike > > ________________________________ > From: SIPTA <sipta-bounces(a)idsia.ch> on behalf of Abrams, Marshall > <mabrams(a)uab.edu> > Sent: Tuesday, 13 November 2018 3:18:37 PM > To: sipta(a)idsia.ch > Subject: [SIPTA] Are there imprecise analogues of pseudo-random number > generators? > > I would like to ask a theoretical and practical question. (No > conference announcement here!) > > tl;dr: Are there imprecise analogues of pseudo-random number generators? > > If that question doesn't make sense, please feel free to read on, with > my thanks for doing so. (Sorry the following is so long; I was worried > that what I was asking would be unclear otherwise.) > > I am interested in imprecise chance, that is, objective imprecise > probability; this idea has been discussed in different ways by > Terrence Fine and his colleagues, Marco Cattaneo, Luke Glynn, Alan > Hajek, Suppes and Zanotti, Stephan Hartmann, Igor Gorban, and probably > others. > > In an agent-based model, (precise) chance can be modeled using a PRNG. > Can this be generalized to base an ABM on a model of imprecise chance? > I had thought this would be impossible, but now I am not so sure. A > good PRNG such as a Mersenne Twister is of course not truly chancy, > and its output even has low Kolmogorov complexity, but it's still a > good way to model chance in many contexts. Why couldn't imprecise > chance be modeled in an ABM using a deterministic algorithm as well? > > What would the output of a pseudo imprecise random number generator > (PIRNG) look like? > > Well, suppose one wrote a function that used a normal PRNG to generate > 0's and 1's with probability 0.7 for 1. Then over most large sets of > outputs, we would find the frequency of 1 to be close to 0.7, and as > we increased the size of such a set, the frequency would usually get > closer to 0.7 > > Similarly, using a PIRNG, one ought to be able to write a function > that generates 0's and 1's with (for example) an interval probability > of [0.6, 0.8] for 1. Then over most large lets of outputs, the > frequency of 1 should lie in or near [0.6, 0.8], and as we increased > the size of such a set, the frequency would remain near [0.6, 0.8] but > would usually wander without settling down to any precise value within > that interval. > > Are there known algorithms that might have this kind of behavior? Or > could this kind of behavior be simulated using PRNGs for sequences > that are not extremely long? i.e. maybe one can write a function > using a PRNG such that over the not-too-long-run, sequences would > appear to be imprecisely chancy, but they would eventually settle down > to precise values in the very very long run. That might be good > enough for some ABMs. > > Or am I just confused? (I think this is not unlikely.) > > Any suggestions about what sort of literature I should look at or what > kinds of keywords to search on would be welcome. > > [In some parts of Fierens, Rego, and Fine's "A frequentist > understanding of sets of measures" (2009), it sounds as if such a > class of algorithms might be described, at least in a loose, general > way, but if that is so, I have not understood the article well enough > to see how what's given there does so. Their model uses sequence > specified to be of intermediate Kolmogorov complexity, which itself > seems like a difficult thing to generate.] > > > Thank you! > > Marshall > > > Marshall Abrams, Associate Professor > Department of Philosophy, University of Alabama at Birmingham > Email: mabrams(a)uab.edu; Phone: (205) 996-7483; Fax: (205) 975-6610 > Mail: HB 414A, 900 13th Street South, Birmingham, AL 35294-1260; > Office: HB 418 > Website: http://members.logical.net/~marshall > > _______________________________________________ > SIPTA mailing list > SIPTA(a)idsia.ch > http://mailman2.ti-edu.ch/mailman/listinfo/sipta > _______________________________________________ > SIPTA mailing list > SIPTA(a)idsia.ch > http://mailman2.ti-edu.ch/mailman/listinfo/sipta _______________________________________________ SIPTA mailing list SIPTA(a)idsia.ch http://mailman2.ti-edu.ch/mailman/listinfo/sipta

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