Positions at the University of Colorado Denver

The Department of Mathematical and Statistical Sciences at the
University of Colorado Denver invites applications for a tenure-track
assistant professor position in Numerical Methods and Scientific
Computing and a tenure-track assistant professor position in
Statistics, to start August 2013.

The Department has 16 tenured or tenure-track faculty members whose
research and teaching cover a wide range of areas, including
computational biology, computational and and engineering mathematics,
probability, statistics, graph theory, combinatorics, operations
research, and optimization. The Department has approximately 70 M.S.
and Ph.D. students, and 100 undergraduate mathematics majors. Many
departmental faculty are involved with the Center for Computational
Mathematics, and the University owns a major TOP50 supercomputing
facility with large reserved allocations available.

The regular teaching load is 4 undergraduate or graduate courses per
year, which may be reduced for an initial period. The candidate will
be expected to develop a strong independent research program with
external funding and to teach a variety of courses at both the
graduate and undergraduate levels. A completed doctoral degree, or
expected completion by the start of the appointment, is required.

The candidate should have an excellent record in research commensurate
with the career stage, and strong commitment to quality teaching at
both undergraduate and graduate levels. Further preference will be
given to candidates with demonstrated potential for attracting
external research funding and with research interests compatible with
present faculty research areas which include numerical solutions of
partial differential equations, numerical linear algebra, parallel
computing, mathematical modeling involving systems of PDEs or
stochastic PDEs, data assimilation, quantification of uncertainty,
extreme value theory, high-dimensional data, spatial statistics,
statistical genetic and genomics, Bayesian statistics, and
environmental and ecological applications. In addition, an interest in
interacting with faculty in other research areas in the department
and/or University would be desirable.

Salary is commensurate with skills and experience. The University of
Colorado offers a full benefits package.  Information on University
benefits programs, including eligibility, is located at
http://www.cu.edu/pbs/

Applications are accepted electronically at www.jobsatcu.comunder job
posting 819515 (numerical
http://www.jobsatcu.com/applicants/Central?quickFind=70811) and 819855
(statistics http://www.jobsatcu.com/applicants/Central?quickFind=71151).
Review of applications will begin January 7, 2013 and will continue
until the position is filled. The Department web page at
http://math.ucdenver.edu/ can supply further information.

The University of Colorado Denver is dedicated to ensuring a safe and
secure environment for our faculty, staff, students and visitors. To
assist in achieving that goal, we conduct background investigations
for all prospective employees.

The University of Colorado strongly supports the principle of
diversity. We encourage applications from women, ethnic minorities,
persons with disabilities and all veterans.

Presolve and statuses CPX_STAT_INForUNBD or IloCplex::InfOrUnbd.

When using mip solver , it is often to encounter cases where a specific optimization model is either infeasible or unbounded (CPX_STAT_INForUNBD in CPLEX).  Here is a nice post on this topic which provides insight on this flag message. 

http://www-01.ibm.com/support/docview.wss?uid=swg21399996

Faculty Opening at Department of Computational and Applied Mathematics (CAAM) Rice University

Department of Computational and Applied Mathematics (CAAM)
Rice University

The Department of Computational and Applied Mathematics
(http://www.caam.rice.edu/) invites applications for a tenure track
professorship beginning July 1, 2013. Candidates at the assistant
professor level are preferred, although outstanding candidates at all
levels will be considered. The Department offers an outstanding
research environment and hosts research programs in optimization,
numerical linear algebra, control and inverse problems, partial
differential equations, and scientific computing. Interdisciplinary
work is a fundamental aspect of the Department's program.

Preference will be given to candidates who are engaged in
high-performance computing and whose research complements existing
strengths of the Department. Candidates for this position should have
a PhD and have demonstrated potential for excellence in both research
and teaching.

Applications consisting of a letter of application, current curriculum
vitae containing a list of publications, a description of research,
and a statement on teaching should be submitted via the website
www.MathJobs.Org. In addition, candidates should arrange for at least
three letters of recommendations, which may be submitted on the same
website.

Alternatively, applications and letters of recommendations may be sent
by mail to:

Faculty Search Committee
Department of Computational and Applied Mathematics (CAAM)
Rice University
6100 Main Street, MS-134
Houston, TX 77005-1827

PLEASE DO NOT DUPLICATE YOUR APPLICATION!

To receive full consideration the complete application must be
received by January 11, 2013, but the committee will continue to
accept applications until the position is filled.

Rice University is an affirmative action/equal opportunity employer.

_____________________________________________________
Matthias Heinkenschloss
Professor and Department Chair

Department of Computational and Applied Mathematics - MS 134
Rice University
Houston, Texas 77005, USA

Phone 713-348-5176
Fax      713-348-5318
http://www.caam.rice.edu/~heinken

2 Two Year Postdoctoral Positions in Cambridge, UK

Cambridge Systems Associates Limited (CSA), a small high end financial services analytics, consulting and software company (see www.cambridge-systems.com), has two 2 year postdoctoral positions, funded by the EU and starting as soon as possible.

The full time R&D work will involve development of CSA's iALM financial planning system and its patented STOCHASTICS stochastic optimization analyst software in high performance computing applications. Publications from the work will be expected.

Lloyds Banking Group and Citigroup are the financial partners and Numerical Applications Group (NAG), Maxeler and several leading European Universities are other partners on the EU High Performance Computing in Finance (HPC Finance) project. Please see the project website: www.hpcfinance.eu for a full list of partners, where CSA's detailed job descriptions may also be found (dates on these latter are irrelevant).

We are seeking recent PhDs (not more than 4 years from doctoral completion) in mathematics, statistics, OR, computer science or quantitative finance. Candidates must not be UK citizens, nor have spent more than one year in the UK to date.

The successful applicants will be CSA employees and salaries are generous, with moving allowances available. The active and exciting environment for these positions is Cambridge University. The company's elegant offices are in the centre of the University and the city.

Interested candidates should apply to Professor M.A.H. Dempster (mahd2@cam.ac.uk) at their earliest convenience.

An Effective and Time-efficient Approach to Solving Linear Discrete Optimization Problems using Discretized Network Flow

A recent NSF grant is award to Shantanu Dutt. Here is the abstract below from the NSF website

Discrete optimization finds widespread use in almost all areas of human endeavor ranging from science to technology to business, and encompassing diverse applications such as chip design, power system design, robotics, bioinformatics, transportation, financial computing and industrial engineering. However, currently there is no general discrete optimization solver that can solve hard problems near-optimally in tractable runtimes (fast to moderate runtimes). To rectify this, this project will explore developing novel and efficient techniques for solving the class of 0/1 integer linear programming (ILP) problems that can be used to model a wide range of discrete optimization problems (DOPs). The approach used for this purpose is a solution technique termed discretized network flow (DNF), in which classical network flow (that solves a class of continuous linear programming problems), is constrained by special discrete requirements on the flow to yield valid solutions to 0/1 ILPs.

A successful completion of this project will yield algorithms and a software tool for solving large 0/1 ILP problems near-optimally and much faster than current techniques. This will represent a significant advance in the state-of-the-art of such solvers, and can be used to solve large DOPs more accurately and faster in many application areas ranging from genomics to chip design to robotics. This can help in answering fundamental issues in these application areas that have not been attempted so far, and also lead to better products and services in these areas. For example, in the area of chip design, the use of our solver can lead to much lower power and higher quality chips (e.g., with good performance and reliability) than are possible with current CAD tools, and thereby result in better and greener electronic products in several consumer and commercial application areas.

Optimization without Round-off Errors

Recently, a NSF grant is awarded to Erick Moreno-Centeno on Optimization without Round-off Errors. It will be thrilling in the community since round-off erros have been a serious concern to solve large scale optimization problems, especially those with integer variables.

This Early-concept Grant for Exploratory Research (EAGER) provides funding to further develop an algorithm to solve systems of linear equations with a specific advantage over Gaussian Elimination in that the algorithm does not have round-off errors. The algorithm will be tailored and adapted to be used within existing optimization algorithms. The key property of the algorithm being further developed is that it maintains the integrality of the numbers throughout its execution. In particular, although the algorithm does contain divisions (which is crucial for the polynomial-time complexity of the

algorithm) all the divisions have a remainder of zero. A detailed complexity analysis of the algorithm will be performed; specifically, both its running time and the number of bits required to represent the numbers throughout the algorithm's execution will be investigated. A modification of the algorithm to perform LU factorizations will also be studied. Finally, the algorithm will be adapted to enable its use for the basis updates performed in state-of-the-art implementations of the revised simplex method.

If successful, the outcomes of this research will lead to a deeper understanding of computational linear algebra free of round-off errors and the associated applications within optimization algorithms. In the linear programming (LP) context, this research will enable us to solve large-scale LPs exactly; this, in turn, will significantly improve the accuracy and speed of integer programming solvers. In addition, since solving systems of linear equations is a critical subroutine of many numerical algorithms, this research will impact many application areas where linear systems frequently arise, including economics, physics, chemistry, and engineering.

postdoctoral position in Carnegie Mellon University

A postdoctoral position is available in my group in the area of computational global optimization.  I am looking for a person interested to work on the development and implementation of polyhedral cutting plane techniques for nonlinear and mixed-integer nonlinear problems in the context of the BARON project.  For current group activities, see http://archimedes.cheme.cmu.edu  Those interested in this position, please email me your CV/papers and let me know if you are available to meet during the INFORMS meeting in Phoenix.

Best wishes, Nick Sahinidis