Subject: NA Digest, V. 19, # 21

NA Digest  Tuesday, May 28, 2019  Volume 19 : Issue 21

Today's Editor:

	Daniel M. Dunlavy
	Sandia National Labs
	[log in to unmask]

Today's Topics:

	Piet Hemker, 1941-2019
	MFEM Version 4.0
	Release Note, OpenLB Version 1.3
	New Book, Mastering Frequency Domain Techniques ...
	New Book, Passive Network Synthesis: An Approach to Classification
	Machine Learning and Uncertainty Quantification, USA, Jul 2019
	Modelling the Cardiac Function, Italy, Jul 2019
	Computational Mathematics and Applications, USA, Oct 2019
	SIAM Central States Meeting, USA, Oct 2019
	Full Professorship Position, Stochastic Analysis
	Professorship Position, Mathematical Optimization, TU Dresden
	Tenure-Track Lecturership Position, Applied Mathematics, LIverpool
	Researcher Position, Uncertainty Quantification, Technical Univ of Denmark
	Postdoc Position, Computational Math, Morgan State Univ
	Postdoc Position, Distributed Algorithms for ML and IR, Inria
	Postdoc Position, High-Order Methods for Conservation Laws, McGill Univ, Canada
	Postdoc Position, Mathematics, Univ of Trento
	Postdoc Position, Univ of Coimbra, Portugal
	Postdoc Position, Univ of Manchester
	Postdoc Positions, Math Imaging/Optimization/Inv Problems, Shenzhen Univ
	PhD Position, Efficient and robust reservoir simulation
	PhD Position, NA/Scientific Computing, Univ of Innsbruck
	Contents, Siberian J of Numerical Mathematics, 22 (2)

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Submissions for NA Digest:
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From: Kees Oosterlee [log in to unmask]
Date: May 28, 2019
Subject: Piet Hemker, 1941-2019

It is with great sadness that we let you know that on 27 May professor
Piet Hemker passed away, at the age of 77 years.

Piet worked at CWI - Center for Mathematics & Computer Science, in
Amsterdam, the Netherlands, from 1970 until his retirement in
2006. Since 1989 until his retirement, he has also been an endowed
professor at the UvA. Since 2001 he was a CWI Fellow.

Piet has helped to shape numerical mathematics in the Netherlands for
many years. He contributed with important innovative scientific
research to, among others, multigrid methods, defect correction,
numerical methods for compressible flows, and manifold mapping. Even
after his retirement, Piet was still often actively present at
seminars, thinking along with numerical mathematics problems.

We will miss him tremendously and remember him with great gratitude.

Sincerely,
Kees Oosterlee, Barry Koren

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From: Tzanio Kolev [log in to unmask]
Date: May 25, 2019
Subject: MFEM Version 4.0

Version 4.0 of MFEM, a lightweight, general, scalable C++ library for
finite element methods, is now available at: http://mfem.org

The goal of MFEM is to enable high-performance scalable finite element
discretization research and application development on a wide variety
of platforms, ranging from laptops to exascale supercomputers.

For the first time ever, MFEM-4.0 adds support for GPU acceleration:
- Device kernels can be written in CUDA, OCCA, RAJA or OpenMP.
- Several examples have been ported with minimal code changes.
- Many linear algebra and finite element operations can use device
  acceleration by simply replacing loops with MFEM_FORALL.
- The library provides seamless device/host memory management.

Some other additions in version 4.0 are:
- Partial assembled finite element operators in the core library.
- Support for prism elements and meshes with mixed element types.
- General "low-order refined"-to-"high-order" field transfer.
- Seven new examples and miniapps.

The MFEM library has many more features, including:
- 2D and 3D, arbitrary order H1, H(curl), H(div), L2, NURBS elements.
- Parallel version scalable to hundreds of thousands of MPI cores.
- Conforming/nonconforming adaptive mesh refinement (AMR), including
  anisotropic refinement, derefenement and parallel load balancing.
- Galerkin, mixed, isogeometric, discontinuous Galerkin, hybridized,
  and DPG discretizations.
- Support for triangular, quadrilateral, tetrahedral and hexahedral
  elements, including arbitrary order curvilinear meshes.
- Scalable algebraic multigrid, time integrators, and eigensolvers.
- Lightweight interactive OpenGL visualization with the MFEM-based
  GLVis tool.

MFEM is being developed in CASC, LLNL and is freely available under
LGPL 2.1. For more details, see the interactive documentation and the
full CHANGELOG.

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From: Mathias Krause [log in to unmask]
Date: May 21, 2019
Subject: Release Note, OpenLB Version 1.3

The OpenLB developer team is very happy to announce that a new release
of the open source Lattice Boltzmann Method (LBM) code is available
for download on the project website https://www.openlb.net. New
examples and models for multi-component fluid flow simulations and
many user-friendly interfaces have been added.Have a look and be
excited!

PS: Please consider joining the developer team, by contributing your
code and strengthen the LB community by sharing your research in an
open and reproducible way!


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From: Kris ONeill [log in to unmask]
Date: May 21, 2019
Subject: New Book, Mastering Frequency Domain Techniques ...

Mastering Frequency Domain Techniques for the Stability Analysis of
LTI Time Delay Systems
Rifat Sipahi

This multipurpose book addresses the following questions for linear
time- invariant (LTI) systems with an eigenvalue-based approach that
is built upon frequency domain techniques: the fundamental question of
how to study the stability of dynamical systems influenced by time
delays; the related issues of how much time delay the system can
withstand without becoming unstable; and how to change parameters to
render improved dynamic characteristics, utilize/tune delay to improve
dynamical behavior, and assess the stability and speed of response of
the dynamics. Readers will find key results from the literature,
step-by-step demonstrations of all implementations, and Maple and
MATLAB code that is available from the author's website.

2019 / xviii + 174 pages / Softcover / 978-1-611975-71-0 / List $74.00
/ SIAM Member $51.80 / CS20

See more details here: http://bookstore.siam.org/cs20

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From: Kris ONeill [log in to unmask]
Date: May 21, 2019
Subject: New Book, Passive Network Synthesis: An Approach to Classification

Passive Network Synthesis: An Approach to Classification
By Alessandro Morelli and Malcolm C. Smith

A resurgence of interest in network synthesis in the last decade,
motivated in part by the introduction of the inerter, has led to the
need for a better understanding of the most economical way to realize
a given passive impedance. This monograph outlines the main
contributions to the field of passive network synthesis and presents
new research into the enumerative approach and the classification of
networks of restricted complexity. It serves as both an ideal
introduction to the topic and a definitive treatment of the Ladenheim
catalogue.

May 2019 / vi + 153 pages / Softcover / 978-1-611975-81-9 / List
$64.00 / SIAM Member $44.80 / DC33

See more details here: http://bookstore.siam.org/dc33

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From: Dongbin Xiu [log in to unmask]
Date: May 28, 2019
Subject: Machine Learning and Uncertainty Quantification, USA, Jul 2019

Research Challenges and Opportunities at the interface of Machine
Learning and Uncertainty Quantification
July 24-26, 2019, University of Southern California, USA
http://hyperion.usc.edu/MLUQ/

The fast growth in practical applications of machine learning (ML), in
a range of contexts including, e.g. physical, cyber, and socioeconomic
systems, has fueled a renewed interest in ML methods over recent
years.  These advances and achievements depend on the availability of
(1) effective algorithms, (2) significant computational capabilities
and (3) large volumes of data. Despite the demonstrated successes of
ML, it is well recognized that the reliability of ML decisions is
often strongly impacted by data errors/noise, data gaps and partial
data, modeling errors, and generalization. Accordingly, significant
research efforts are targeted at probabilistic ML (PML) methods, to
enable the quantification of uncertainty in trained ML model
parameters and predictions. The technical challenges in PML are
similar to those faced in the field of uncertainty quantification
(UQ). The two fields share difficulties with both training/parameter-
estimation and forward prediction, when dealing with large models with
many parameters, fundamental modeling uncertainties, large data that
is nonetheless often insufficiently informative, data gaps and
partial/missing data, data errors and noise, dangers of overfitting,
and computational costs. The purpose of this workshop is to provide a
forum for exchange of information from experts in each of these two
communities, exposing and discussing challenges, opportunities, and
potential future research directions for advancing the state of the
art across both domains.

List of Topics Probabilistic methods in machine learning; Bayesian
networks; Network inference; Missing, partial and sparse data; Sparse
low rank constructions; Probabilistic machine learning in high
dimensions; Uncertainty quantification in machine learning training
and prediction; Machine learning methods in uncertainty
quantification.

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From: Luca Paglieri [log in to unmask]
Date: May 20, 2019
Subject: Modelling the Cardiac Function, Italy, Jul 2019

2019 RISM Congress
iHEART - Modelling the Cardiac Function
22-24 July 2019 - Varese (Italy)

Chair: Alfio Quarteroni
Abstract submission deadline: May 31, 2019
http://iheart.polimi.it/mcf2019

This congress, organised in the context of the prestigious Riemann
International School of Mathematics, aims at focusing on the state of
the art in the mathematical modelling and numerical simulation of the
cardiac function and its clinical applications.

This event will host plenary lectures from distinguished scientists as
well as contributed talks, some presented by PhD students and some by
senior researchers, and a poster session. PhD students selected for
contributed presentation will be offered free accommodation.

Plenary speakers: Dominique Chapelle (INRIA, FR), Antonio F. Corno
(U. Leicester, UK), Miguel Fernandez (INRIA, FR), Antonio Frontera
(H. San Raffaele Milano, IT), Rolf Krause (USI, CH), Gernot Plank
(U. Graz, AT), Nicholas Smith (U. Auckland, NZ), Natalia Trayanova
(Johns Hopkins U., USA)

For more information and registration form:
http://iheart.polimi.it/mcf2019


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From: Jichun Li [log in to unmask]
Date: May 22, 2019
Subject: Computational Mathematics and Applications, USA, Oct 2019

We are pleased to invite you to participate in "Conference on
Computational Mathematics and Applications" to be held at University
of Nevada Las Vegas (UNLV), October 25 - 27, 2019. The conference aims
at bringing together computational scientists from several disciplines
to exchange new computational methodology and exciting applications
developed recently.

The themes of the conference include, but not limited to, topics:
Numerical methods for wave propagation and applications; Numerical
studies for fluid flow modelling, interface problems and applications
to fluid-structure interactions (FSI); New technology and applications
of finite element methods; Numerical methods for stochastic PDEs and
applications; Uncertainty qualification and big data; Machine Learning
for Scientific Computing.

Plenary Speakers (confirmed) are: Susanne Brenner (Louisiana State
University); Chi-Wang Shu (Brown University); Peter Monk (Univsity of
Delaware); George Karniadakis (Brown University); Thomas J.R.  Hughes
(University of Texas - Austin).

The conference is partially supported by NSF, UNLV Math Dept, and
"Results in Applied Mathematics"
(https://www.journals.elsevier.com/results-in-applied-mathematics).
Limited financial supports are available for local lodging. We
encourage Ph.D students, junior faculty and under-represented groups
to apply by June 30.

For more information, please visit the conference website:
http://cams.sites.unlv.edu/conferences/ccma2019/ccma2019.html.

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From: James Rossmanith [log in to unmask]
Date: May 23, 2019
Subject: SIAM Central States Meeting, USA, Oct 2019

Call for Minisymposium Proposals for 2019 SIAM Central States Annual
Meeting

Announcing the 2019 SIAM Central States Annual Meeting!
When: October 19th and 20th, 2019
Where: Iowa State University, Ames, Iowa
Url: https://siam2019.math.iastate.edu

Important Dates:
- May 21, 2019: Abstract submission opens for minisymposium organizers
- June 30, 2019: Mini-symposium proposal deadline for organizers
- August 8, 2019: Abstract submission deadline for a talk in a
  minisymposium
- August 31, 2019: Early bird conference registration deadline
- September 13, 2019: Financial support applications are due

We are currently soliciting submissions of Minisymposium Proposals.
Minisymposium Proposals can be submitted at the following website:
https://siam2019.math.iastate.edu/submissions.html

NOTE: Each Minisymposium Proposal should consist of 1 to 2 organizers
and 4 to 8 speakers. Please make sure to obtain consent from your
speakers before listing them.  You will also need a tentative title
for each speaker. Additional speakers may be added to your
minisymposium once the general abstract submission has been completed
-- we will work closely together with the minisymposium organizers
during the phase of the conference organization.

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From: Imke Franzmeier [log in to unmask]
Date: May 27, 2019
Subject: Full Professorship Position, Stochastic Analysis

The Faculty of Mathematics and Computer Science and the Cluster of
Excellence Mathematics Munster: Dynamics - Geometry - Structure at the
University of Munster, Germany, invite applications for a Full
Professorship in Stochastic Analysis, Bridging the Gaps Professorship,
W3 level. This professorship has been established in the context of
the new Cluster of Excellence Mathematics Munster within the framework
of the German Excellence Strategy. In the Bridging the Gaps
Professorship, the chosen candidate is expected to play a major role
in connecting mathematical fields of the participating institutes, for
instance between the Institute for Mathematical Stochastics and the
Institute for Analysis and Numerics.  We are looking for a dynamic and
committed personality with an outstanding research profile in the
field of stochastic analysis.  Special attention will be given to
candidates who can demonstrate their ability to enhance and complement
the existing research groups at Mathematics Munster and are open to
interdisciplinary collaborations with other scientific groups at the
University of Munster. A visible role in intra- and interdisciplinary
co-operations with existing and planned third-party funded projects
and research centres is expected, as well as participation in our
study programmes.  Prerequisites for the application are a doctoral
degree in mathematics or a related field, outstanding contributions to
stochastic analysis, and corresponding teaching experience.
Additionally prerequisite for the application are academic
achievements made as a Juniorprofessor (assistant professor), in a
Habilitation (postdoctoral qualification), as a member of the academic
staff of a university or non-university research institute, or in a
research position in business, administration or other relevant fields
in Germany or abroad. The University of Munster is an equal
opportunity employer and is committed to increasing the proportion of
women academics.  Consequently, we actively encourage applications by
women. Female candidates with equivalent qualifications and academic
achievements will be preferentially considered within the framework of
the legal possibilities. We also welcome applications from candidates
with severe disabilities. Disabled candidates with equivalent
qualifications will be preferentially considered.

Applications, including a CV, list of publications, research plan, and
teaching portfolio, should be submitted electronically as a single PDF
file by 30 June 2019 to [log in to unmask]

Please find more information on www.mathematics-muenster.de

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From: Oliver Sander [log in to unmask]
Date: May 20, 2019
Subject: Professorship Position, Mathematical Optimization, TU Dresden

The Technical University Dresden in Dresden, Germany is currently
offering a permanent professorship position (W2) in mathematical
optimization. This is an interesting position at an interesting place,
and people with a strong background in any branch of optimization are
kindly invited to apply.

More information at
https:/tu-dresden.destellenausschreibung6801 (Ger.)
or
https:/www.verw.tu-dresden.deStellAusstelle.asp?id=6801&lang=en (Engl.)

Deadline is 21 jun 2019.

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From: Ke Chen [log in to unmask]
Date: May 23, 2019
Subject: Tenure-Track Lecturership Position, Applied Mathematics, LIverpool

We are seeking to appoint a Lecturer initially for 3 years with the
possibility to become permanent after competitive evaluation after 2+1
years in the area of Applied Mathematics (mainly Waves, Math Biology
or Math Imaging).  Three other posts in areas of Pure Math,
Stochastics and Theoretical Physics) may be found form searching the
page https://recruit.liverpool.ac.uk/. All the posts will be held in
the Department of Mathematical Sciences, which is part of the School
of Physical Sciences at the University of Liverpool.

Deadline: 13-Jun-2019 23:30
Further details: https://tinyurl.com/Liverpool-Jun13th


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From: Per Christian Hansen [log in to unmask]
Date: May 21, 2019
Subject: Researcher Position, Uncertainty Quantification, Technical Univ of Denmark

The Technical University of Denmark opens a permanent entry-level
position as researcher, starting Sept. 1, 2019 (or as soon as possible
after that). The position is part of the research project CUQI,
Computational Uncertainty Quantification for Inverse Problems.  For
details see: https://www.compute.dtu.dk/english/cuqi

We seek a candidate to develop a modeling platform and a flexible
software system that performs Uncertainty Quantification (UQ) for
inverse problems. Specifically, the applicant will be responsible for
the development of a framework that turns UQ for inverse problems into
an operational tool, consisting of:
- A modeling platform to formulate and utilize many prior models.
- A software system that utilizes the user's specific solution codes.
This task involves a combination of theory development, algorithm
design, software implementation, and test/validation on use-cases.

A central theme in computational UQ is to formulate mathematical
models for the priors such that they are practical and computationally
useful. It is desirable to have a general modelling approach that
works for a range of different types of prior models. The main
challenge is to design and build such a general system; additional
challenges are how to store and represent the underlying UQ
information, and how to visualize it in an intuitive way.

The development of this framework combines elements of inverse
problems theory, Bayesian modeling, numerical analysis, optimization,
software development, and validation. The result is a user-friendly
abstraction level that lets users focus on modeling and data analysis,
instead of mathematical details and low-level algorithm aspects.  For
more details and to apply: https://tiny.cc/CUQI-Researcher


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From: Mingchao Cai [log in to unmask]
Date: May 20, 2019
Subject: Postdoc Position, Computational Math, Morgan State Univ

Postdoctoral Position in Computational Math at Morgan State University

A postdoctoral position in CComputational Math is available at Morgan
State University in the department of Mathematics.  The work involves
Finite element methods and numerical analysis for fluid poroelastic
structure interactions. Candidates should have a Ph.D degree in
Computational Mathematics or in Engineering with background in Finite
Element methods, high performance computing, fluid mechanics, and/or
structure mechanics. The position is available now and is expected to
be filled as soon as possible. The benefit include regular salary
($3,200/m) plus insurance ($1,000/m charged by Morgan State
University).  The regular salary part is negotiable based on the
expertise of the candidates. Interested candidates should contact
Professor Mingchao Cai (see address below) with a CV and a description
of their background and research interests.

Professor Mingchao Cai
Department of Mathematics
Morgan State University
1700 E Cold Spring Ln, Baltimore, MD, 21251

E-mail: [log in to unmask]

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From: Konstantin Avrachenkov [log in to unmask]
Date: May 22, 2019
Subject: Postdoc Position, Distributed Algorithms for ML and IR, Inria

Topic of postdoc project: Asynchronous distributed algorithms for
information retrieval and machine learning

Resume: Many tasks in information retrieval (IR) and machine learning
(ML) require operation with very large volumes of data, often
distributed across distant databases. This calls for development of
asynchronous distributed algorithms. Let us mention just a few typical
tasks in IR and LM that require distributed approaches to process the
data: PageRank, databases update and synchronization, distributed
(federated) machine learning. Most existing distributed approaches for
the mentioned tasks are either not asynchronous or have slow
convergence. Thus, we aim to design, to analyse and to test rapidly
convergent asynchronous distributed approaches.

Requirements: PhD in Mathematics, Computer Science or Electrical
Engineering; Solid background in Linear Algebra, Optimization,
Probability and Statistics; Knowledge of Python as working programming
language is another requirement. Experience in machine learning or
information retrieval is a plus.

For more information visit:
https://jobs.inria.fr/public/classic/fr/offres/2019-01636


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From: Sivakumaran Nadarajah [log in to unmask]
Date: May 20, 2019
Subject: Postdoc Position, High-Order Methods for Conservation Laws, McGill Univ, Canada

Postdoc position is available within the Computational Aerodynamics
Group at the Department of Mechanical Engineering, McGill University,
Montreal, Canada. Successful candidates will pursue a research agenda
in the area of High-Order Space-Time Methods for Hyperbolic
Conservation Laws. The envisioned starting date for the position is
July-September 1, 2019, or soon thereafter. Funding at 100% is
available for a two-year period.

For further details on the research group, please see
https://sites.google.com/view/mcgill-computational-aerogroup/home?authuser=0

Apply to [log in to unmask] by June 30, 2019.

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From: Lucas Omar Muller [log in to unmask]
Date: May 24, 2019
Subject: Postdoc Position, Mathematics, Univ of Trento

Applications are invited for a post-doctoral research fellow position
at the Department of Mathematics, University of Trento (Italy).

Candidates from almost all branches of mathematics, including
Numerical Analysis, are welcomed. A research proposal, in line with
one of the research activities of the Department, has to be presented.

Further information and instructions on how to apply can be found at
https://www.unitn.it/en/ateneo/bando/58105/department-of-mathematics-call-for-the-
selections-for-the-awarding-of-no-1-research-fellowship-decre

Further inquires, especially for applicants with interest in Numerical
Analysis research topics, can be send to [log in to unmask]

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From: Isabel Narra Figueiredo [log in to unmask]
Date: May 22, 2019
Subject: Postdoc Position, Univ of Coimbra, Portugal

Postdoctoral position in computational mathematics (focusing on image
processing and analysis, visualization, numerical analysis,
optimization, inverse problems in imaging, partial differential
equations - with applications in medicine) in the framework of the
interdisciplinary research project "Multi-Cam Capsule Endoscopy
Imagery: 3d Capsule Location and Detection of Abnormalities", with
reference POCI-01-0145-FEDER-028960, of FCT - Portuguese national
funding agency for science, research and technology
(https://www.fct.pt/index.phtml.en)

Location : Department of Mathematics, Faculty of Sciences and
Technology,   University of Coimbra (Coimbra) Portugal.

Duration : 1 year (possible extension - extra 1 year).

Starting date : October 2019.
Applications : June 03 - June 17, 2019.

Detailed information :
http://www.mat.uc.pt/~isabelf/Postdoccall2019.html

Official announcement :
http://www.eracareers.pt/opportunities/index.aspx?task=global&jobId=114477

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From: Kody Law [log in to unmask]
Date: May 23, 2019
Subject: Postdoc Position, Univ of Manchester

There is a postdoctoral research associate position opening at
University of Manchester, in the area of microstructure image
recognition and feature extraction, a.k.a. digital fingerprinting of
materials microstructure.

The appointment will be in the School of Mathematics in the Inverse
Uncertainty Quantification Group, and joint with the Henry Royce
Institute for Advanced Materials. The project is linked to the Data
Centric Engineering Programme at The Alan Turing Institute.

Please follow this link for the official advert, as well as further
particulars and application instructions. Feel free to email me
directly with inquiries.

https://www.jobs.manchester.ac.uk/displayjob.aspx?jobid=17333

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From: J. Lu [log in to unmask]
Date: May 28, 2019
Subject: Postdoc Positions, Math Imaging/Optimization/Inv Problems, Shenzhen Univ

Postdoc Positions in Shenzhen University, China
Location: Shenzhen, China
Job Type: Full-Time
Duration: 2 years
Number of Position: 4 Positions
Closing Date: Open Until Filled

Description: We are looking for Postdoctoral Researchers in
Image/Video Processing/Analysis,Mathematical Imaging, Optimization,
Inverse Problems, Wavelet analysis, etc.

We have no teaching tasks and check in / check out policy for
Postdoctoral Researchers.

Promotors:
- Prof. Jian Lu (Shenzhen Key Laboratory of Advanced Machine Learning
  and Applications, College of Mathematics, Shenzhen University)
- Prof. Lixin Shen (Syracuse University, USA)

The salary is about 330,000 RMB (49,000 US dollars) per year, of which
180,000 RMB per year is after-tax. Those who are interested please
send their C.V. to Prof. Dr. Jian Lu, e-mail: [log in to unmask];
[log in to unmask]


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From: Xing Cai [log in to unmask]
Date: May 27, 2019
Subject: PhD Position, Efficient and robust reservoir simulation

Simula Research Laboratory, Norway, invites applications for a 3-year
PhD position in the subject of efficient and robust reservoir
simulation.

Detailed info:
https://www.simula.no/about/job/call-phd-student-efficient-and-robust-reservoir-simulation

Application deadline: July 7, 2019
Start time: As soon as possible (no later than October 1, 2019)

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From: Lukas Einkemmer [log in to unmask]
Date: May 24, 2019
Subject: PhD Position, NA/Scientific Computing, Univ of Innsbruck

The numerical analysis group [1] at the University of Innsbruck
invites applications for a PhD position within the framework of the
FWF project 'Exponential Integrators for Problems in
Magnetohydrodynamics' (P 32143), led by Lukas Einkemmer. The main goal
of the project is to develop novel numerical algorithms for problems
in plasma physics that are well suited for modern computer systems.

Applications are invited from candidates who have some background in
numerical analysis, numerical linear algebra, scientific and high
performance computing, or related application areas. Experience in C++
and/or parallel programming is particularly welcome (but not
necessary). Applications that arrive before 31.07.2019 will be given
preferential treatment.

To apply please send your cv to [log in to unmask]

The successful applicant will be employed as a 'Doctoral candidate'
per FWF salaries [2] (2,162.40 Euro gross salary, 14 times a year).

[1] https://numerical-analysis.uibk.ac.at/
[2] https://fwf.ac.at/en/research-funding/personnel-costs/

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From: Siberian Journal of Numerical Mathematics [log in to unmask]
Date: May 22, 2019
Subject: Contents, Siberian J of Numerical Mathematics, 22 (2)

CONTENTS, Siberian Journal of Numerical Mathematics
Volume 22, No. 2, 2019

For information to contributors and about subscriptions
see http://www.sscc.ru/SibJNM/

Kel'manov A.V., Panasenko A.V., Khandeev V.I., Exact algorithms of
searching for the largest size cluster in two integer 2-clustering
problems

Koledina K.F., Koledin S.N., Gubaydullin I.M., Automated
identification system conditions for homogeneous and heterogeneous
reactions in multy-purpose optimization problems

Kudinov I.V., Kotova E.V., Kudinov V.A., A method of obtaining
analytical solutions to boundary value problems based on the
definition of additional boundary conditions and additional required
functions

Liu C., Hou T., Two-grid methods for a new mixed finite element
approximation of semilinear parabolic integro-differential equations

Mikhailov G.A., Randomized algorithms of the Monte Carlo method for
problems with random parameters (``double randomization'' method)

Stonyakin F.S., Some adaptive analog of Yu.E. Nesterov's method for
variational inequalities with a strongly monotone operator

{Shakti D., Mohapatra J., {Parameter-uniform numerical methods for a
class of parameterized singular perturbation problems

Shutyaev V.P., Parmuzin E.I., Sensitivity of functionals with respect
to observation data in a variational assimilation problem for the sea
thermodynamics model


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