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PhD position at University of Strathclyde on novel preconditioned iterative solvers for radial basis function linear systemsPosted to SIAG/LA: December 4, 2017.
Applications are invited for a fully funded 3 year PhD studentship in numerical linear algebra, under the supervision of Dr Jennifer Pestana and Dr Alison Ramage, at the Department of Mathematics and Statistics at the University of Strathclyde, Glasgow, Scotland. The project will begin 1 March, 2018, or earlier by arrangement.
Radial basis functions (RBFs) have several advantages when used to numerically approximate the solution of partial differential equations (PDEs) in applications. However, solving linear systems that arise within RBF-based solvers is challenging. This project will develop and mathematically analyse new preconditioned iterative solvers of these linear systems, and will test their performance on interesting applications.
Mathematical modelling is increasingly used to investigate and understand phenomena and forecast future events, particularly when experimentation is prohibitive or costly. However, real-world problems are often posed on complicated domains and involve scattered data, e.g. in geophysical and biological applications, or are inherently high-dimensional, e.g. in quantum physics, finance and systems biology.
Complex geometry, scattered data and high dimensionality can be difficult for some numerical methods for PDEs to deal with. However, these problem features are handled relatively easily by radial basis function approaches. RBF methods represent the solution of PDEs as a combination of radial basis functions that can be placed anywhere in the computational domain. The suitability of RBFs for complex problems is evidenced by their use in applications, including fluid flow, geophysics, plasma physics, finance and biology.
Despite their advantages for dealing with complex, real-world problems, RBF methods can be difficult to implement. This is because obtaining the combination of radial basis functions that describes the PDE solution requires the solution of one or more challenging (i.e. ill-conditioned) systems of linear equations.
This project will develop effective solvers for linear systems in these RBF methods. In particular, we will focus on certain iterative methods (Krylov subspace methods) that start with an initial guess of the solution that is improved at each step. For these ill-conditioned RBF problems, finding matrices known as preconditioners that accelerate the solution process are essential. Thus, at the core of this project will be the proposal, and analysis, of new solvers for RBF-based PDE solvers. The preconditioners will be tested on real-world applications.
Applicants should have or expect to obtain a good (I or II(i)) honours degree in mathematics or in a related discipline. This project would suit students with an interest in linear algebra and/or numerical analysis. Experience of numerical mathematics and/or programming would be beneficial, but is not essential.
The successful applicant will be part of a vibrant postgraduate community, and will have access to a range of training opportunities, including the Scottish Mathematical Sciences Training Centre (https://smstc.ac.uk/).
For more information please contact Dr Pestana (firstname.lastname@example.org). Formal application is via the University of Strathclyde postgraduate research application process at
Please ensure that you clearly state your interest in this project with these supervisors when making a formal application.
For full consideration, please apply by January 15, 2018.
The studentship covers UK/EU tuition fees and comes with an annual tax-free stipend at the standard UK rate. International students who can fund the difference between UK/EU and International fee rates are also encouraged to apply.
The University of Texas at San Antonio seeks an innovative and dynamic leader for the Department of Mathematics with demonstrated leadership abilities who will build on departmental strengths, recruit outstanding faculty, promote scholarly initiatives - especially in terms of externally supported grant efforts - and be an advocate to both internal University and external constituencies. UTSA is a vibrant University aspiring to reach Tier One research status. The Department is located within the College of Sciences and offers a Bachelor degree in Mathematics and Masters Programs in Mathematics, Mathematics Education, and Applied Mathematics-Industrial Mathematics. The Department has 22 full-time faculty with diverse interests and expertise and 33 non-tenured track faculty members. The department is committed to growing and expanding its undergraduate and graduate programs and developing a Ph.D. program. UTSA and the Mathematics Department are committed to supporting a growing diverse student body and encourage applications from women, minorities, and individuals with a commitment to mentoring under-represented demographics in the sciences. Opportunities for interdisciplinary interactions and collaborations exist not only within other departments and within colleges at UTSA, but also with the UT Health Science Center San Antonio, Southwest Research Institute, local military bases, and numerous companies including USAA, Boeing, and Rackspace. San Antonio, Texas is a vibrant city of more than 1.5 million people, with significant economic growth, numerous industrial establishments and excellent school districts. The city and the University provide excellent cultural and educational opportunities as well as exceptional employment opportunities.
- Degree Requirements: PhD or equivalent in Mathematics. The area of specialization is open
- Record of earning tenure at an accredited four-year university
- Associate or full professor
- Evidence of administrative experience in a higher education setting (center, department, program, director graduate studies, etc.).
- A strong record of externally funded and recognized research
- Record of teaching effectiveness and mentoring of students including doctoral students
- Record of involvement with national/international organizations
- An ability to work productively with faculty and students from diverse backgrounds
Required Application Materials
- Letter of application/narrative statement that describes, in 1 to 3 pages, applicant’s qualifications for the position and plans for future administrative/research/teaching for the department.
- Teaching agenda/statement (max. 2pages)
- Research agenda/statement (max. 2 pages)
- Curriculum vita
- Provide a minimum of 3 references
- Sample publications (in PDF format): provide work that is representative of research.
- Statement of Administrative Philosophy
Review of completed applications will begin on November 17, 2017 and continue until the position is filled.
All applicants should submit their application materials through the https://jobs.utsa.edu/postings/7626 site.
UTSA is an Affirmative Action/Equal Employment Opportunity Employer. Women, minorities, veterans, and individuals with disabilities are encouraged to apply. Applicants who are selected for interviews must be able to show proof that they will be eligible and qualified to work in the United States by time of hire.
Applications are invited for the DAAD funded postdoctoral fellowship in Data Science at AIMS South Africa under the supervision of Dr Bubacarr Bah, the German Research Chair for Data Science. The research area will be Data Science (in a very broad sense). For further details see: https://www.aims.ac.za/en/opportunities/vacancies/postdoctoral-fellowships
Applications will be submitted through the DAAD portal found here: https://www.daad.de/deutschland/stipendium/datenbank/en/21148-scholarship-database/?origin=136&status=2&subjectGrps=C&daad=1&q=postdoctoral%20fellowship&page=1&detail=57407689#bewerbung%20
PLEASE NOTE: In recognition of the higher cost of living in South Africa compared to other Sub-Saharan African countries, the salary offered by DAAD will be topped-up by AIMS South Africa and the amount of top-up will be negotiated with the candidate.
New York University/Courant Institute of Mathematical Sciences
Department of Computer Science
Tenure Track Faculty Positions
The department expects to have several regular faculty positions and invites candidates at all levels to apply. We will consider outstanding candidates in any area of computer science, in particular in scientific computing, verification, programming languages, machine learning and data science.
Faculty members are expected to be outstanding scholars and to participate in teaching at all levels from undergraduate to doctoral. New appointees will be offered competitive salaries and startup packages. In addition, we fully expect to secure affordable housing for the appointees within a short walking distance of the department. New York University is located in Greenwich Village, one of the most attractive residential areas of Manhattan.
Collaborative research with industry is facilitated by geographic proximity to computer science activities at AT&T, Facebook, Google, IBM, Bell Labs, NEC, and Siemens.
Please apply at https://cs.nyu.edu/webapps/facapp/register
To guarantee full consideration, applications should be submitted no later than December 1, 2017; however, this is not a hard deadline, as all candidates will be considered to the full extent feasible, until all positions are filled. Visiting positions may also be available.
EOE/AA/Minorities/Females/Veterans/Disabled/Sexual Orientation/Gender Identity