[External Email]

Subject: NA Digest, V. 20, # 41

NA Digest  Tuesday, October 27, 2020  Volume 20 : Issue 41

Today's Editor:

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

Today's Topics:

        Feng Kang Prize Announcement
        Domain Decomposition Methods, ONLINE, Dec 2020
        Multi-scale, Multi-physics and Coupled Problems, South Korea, Jan 2021
        Research Group Head Position, Data-driven Control and Optimization
        Research Scientist Position, Alg Modelling & SW Eng, ABB
        Research Assistant Position, WIAS, Germany
        Research Associate Position, SISSA mathLab, Italy
        Instructor Position, Applied/Computational Mathematics, EPFL
        Research Scientist & Postdoc Positions, Simula Research Laboratory
        Postdoc Position, Applied Mathematics
        Postdoc Position, HPC/NA, Max Planck, Germany
        Postdoc Position, HPDA/AI, Max Planck, Germany
        Postdoc Position, Math, Comp, Exp Neuroscience, BCAM
        Postdoc Position, Mathematical models for COVID-19, BCAM
        Postdoc Position, Scientific Computing, Bonn Univ
        Postdoc Position, Tensor Computations, Wake Forest Univ
        PhD Position, Numerical Analysis, Mississippi State Univ
        PhD Position, Numerical Analysis, Univ Leicester
        PhD Positions, Data Science, Univ of Edinburgh
        Call for Papers, Reduced Order Modeling in Geosciences
        Contents, Special Issue, OMS, 60th Birthday of Ya-xiang Yuan

Subscribe, unsubscribe, change address, or for na-digest archives:
        http://www.netlib.org/na-digest-html/faq.html

Submissions for NA Digest:
        http://icl.utk.edu/na-digest/

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From: Rujuan Ding [log in to unmask]
Date: October 26, 2020
Subject: Feng Kang Prize Announcement

The Committee of Feng Kang Prize of Scientific Computing is seeking
applications and nominations for 2021 year. The prize is awarded every
other year to young Chinese Scientists under the age of fifty in China
and abroad for their outstanding researches in numerical analysis and
scientific computing.  Application forms can be obtained by anonymous
ftp from

http://lsec.cc.ac.cn/fengkangprize/contact.html

Deadline for applications and nominations is MARCH 15, 2021.

Please send all materials to

Ms. Ru-Juan Ding
Institute of Computational Mathematics
No.55, East Road, Zhong-Guan-Cun, Beijing 100190, CHINA
Email: [log in to unmask]


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From: Felix Kwok [log in to unmask]
Date: October 25, 2020
Subject: Domain Decomposition Methods, ONLINE, Dec 2020

DD26: Registration closing soon

The 26th International Conference on Domain Decomposition Methods
(DD26), organized by the Chinese University of Hong Kong (CUHK), will
take place ONLINE from December 7 to 12, 2020. To take into account
the various geographical locations of our participants, plenary talks
are scheduled at a time that is reasonable for most time zones, and
parallel sessions are scheduled twice a day in such a way that
participants can attend at least one out of two sessions
comfortably. Also, talks will be recorded for later viewing by other
participants (subject to consent from individual speakers). The full
schedule can be found on the conference website.

This is a gentle reminder that registration will close on October 31,
2020. The registration fees are HKD800 (about USD 100) for regular
participants, and HKD400 (about USD 50) for students. We ask all
speakers at minisymposia and contributed sessions to register by that
date, as we will be obliged to remove unregistered speakers from the
schedule. If you have registered in 2019 and opted to keep your fees
for 2020, there is no need to register again, and you will be
contacted for refund arrangements.

For more information about DD26, please see the conference website at
https://www.math.cuhk.edu.hk/conference/dd26/?Conference-Home

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From: Neda Ebrahimi Pour [log in to unmask]
Date: October 27, 2020
Subject: Multi-scale, Multi-physics and Coupled Problems, South Korea, Jan 2021

Call for Abstract contribution - Deadline extension
Submission deadline: 13th of November 2020 (extended)

Workshop on Multi-scale, Multi-physics and Coupled Problems on Highly
Parallel Systems (MMCP) at HPC Asia 2021, January 20-22, Jeju, South
Korea

This workshop will provide a platform for presentations and
discussions on advances in numerical simulation for complex
multi-scale, multi-physics and coupled problems. The goal of the
workshop is to gather researchers (computer scientists, engineers,
mathematicians, physicists, chemists, biologists, material sciences
etc.) working on different disciplines but all facing challenges in
multi-scale and multi-physics as well as coupled simulations on HPC
systems. The main focus will be set on computational issues regarding
performance and suitability for high-performance
computing. Furthermore, the underlying strategies to enable these
simulations will be highlighted.

Keeping these aims in mind, contributions from all aspects of
engineering applications will be considered. Topics of applications
will include (but not be limited to): Multi-scale problems;
Multi-physics problems; Molecular dynamics; Multi-domain/Concurrency;
Multi-scale and/or multi-physics modelling for biomedical or
biological systems; Novel approaches to combine different scales and
physics models in one problem solution; Challenging applications in
industry and academia, e.g. multiphase flows, fluid-structure
interactions, chemical engineering, material science, biophysics,
automotive industry, etc.; Load balancing; Adaptivity; Heterogeneous
architectures; New algorithms for parallel-distributed computing,
specific to this topic.

More information about this workshop and the submission procedure can
be found on our webpage:
https://www.mb.uni-siegen.de/sts/workshops/mmcp2021/


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From: Heike Sill [log in to unmask]
Date: October 22, 2020
Subject: Research Group Head Position, Data-driven Control and Optimization

Weierstrass Research Group on "Data-driven Control and Optimization"
The Weierstrass Institute for Applied Analysis and Stochastics invites
applications for the Head of a research group (m/f/d) (Ref. 20/21) on
data-driven control and optimization with applications in quantitative
biomedicine, modern materials or sustainable energy. A research
orientation combining optimization with partial differential equations
with mathematically founded artificial intelligence, in particular
machine learning techniques, is of special interest.  The position has
a limited term of three years with the possibility of a renewal upon
evaluation, and it is equipped with funds for research personnel as
well as a budget for scientific travels and guests. The Weierstrass
research group will be part of WIAS' flexible research platform.  We
are looking for a highly motivated early-career scientist with a PhD
and an outstanding record in applied mathematics with an emphasis on
optimization. Applications from females are particularly welcome.

See here for more information: https://short.sg/j/7836197

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From: Thorsten Schindler [log in to unmask]
Date: October 26, 2020
Subject: Research Scientist Position, Alg Modelling & SW Eng, ABB
Corporate Research

You are an expert in algorithmic and numerical modelling as well as
software engineering? You would like to leverage model-based data
analytics, machine learning (statistics/uncertainty quantification)
and artificial intelligence for next generation industrial prototypes?
You want to apply your knowledge in a challenging and fascinating
environment up to full-stack solutions? Then join our team of highly
motivated researchers to develop the foundations for ABB's automation
and electrification systems.

Please find more information on the positions, requirements as well as
online application form at:
https://1brd.ly/NA1Bq?
sharereference=eyJzaGFyZVRva2VuIjoiYmQ3MnJjNHY3b2FmIiwidGVuYW50SWQiOiI4OTlm
ZDU1Yi1kMzgxLTQ1YmEtYTdkNC0yMWUzNmUzYjM1MzMifQ==

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From: Heike Sill [log in to unmask]
Date: October 22, 2020
Subject: Research Assistant Position, WIAS, Germany

WIAS invites in the Research Group 'Laser Dynamics' (Head: PD Dr. Uwe
Bandelow) applications for a Research Assistant (f/m/d) (Ref. 20/22).
to be filled at January 1st, 2021. The position is associated with the
research project "Modeling and Optimization of Semiconductor Lasers
for Quantum Metrology Applications" within the Berlin Mathematics
Research Center MATH+.  The aim of the position is to conduct research
in the field of modeling and simulation of semi-conductor lasers. The
research results shall be published in scientific journals and
presented at conferences. In addition, preliminary work for a
dissertation on the above-mentioned topic may be prepared.
Prerequisite is an above-average master's/diploma or doctoral degree
in physics or mathe-matics.  Knowledge in the field of modeling and
nonlinear dynamics of semiconductor lasers as well as experience with
the theoretical description of stochastic processes (noise) in
opto-electronic devices are beneficial. Moreover, programming skills
and expertise in relevant nu-merical methods are required. The holder
of the position is willing to cooperate with users and subject-related
colleagues.  Please direct your queries to Priv.-Doz. Dr. Uwe Bandelow
([log in to unmask]).  The position is remunerated according
to TVoD and is limited until December 31st, 2021 with a reduced
working time of 29.25 hours per week.  See here for more information:
https://short.sg/j/7854597

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From: Gianluigi Rozza [log in to unmask]
Date: October 25, 2020
Subject: Research Associate Position, SISSA mathLab, Italy

A new open position (12 months) as research associate between SISSA,
International School for Advanced Studies, Mathematics Area, mathLab,
Trieste, Italy (mathlab.sissa.it) and European Commission Joint
Research Centre in Ispra (Varese), Italy
(https://ec.europa.eu/jrc/en/about/jrc-site/ispra) is available with
deadline for the call on November 9, 2020 at 1pm (Rome time):

https://www.sissa.it/bandi/selezione-pubblica-titoli-progetto-conferimento-di-n-1-assegno-
di-ricerca-jrc-area-matematica

Apply here: https://pica.cineca.it/sissa/ar-jrc-mate-52-2020

The position is in the framework of FSE FVG: European Social Fund
program 2014-2020 sponsored by Regione Autonoma Friuli Venezia Giulia
and in cooperation with European Commission Joint Research Centre in
Ispra (Varese), Italy (https://ec.europa.eu/jrc/en/about/jrc-
site/ispra) and it is expected to start as soon as filled (beginning
2021).  The project is "Numerical simulations of human brain
vulnerability to blast loading".

Proven experience in Mathematical modelling, numerical analysis and
simulation for complex systems and industry modelled by PDEs,
computational fluid dynamics for optimisation and control, data
science, data assimilation and uncertainty quantification, scientific
computing programming, high performance computing and/or large scale
computing competences.  Additional requirements, competencies and
abilities: Good knowledge of high level programming languages, e.g.,
C/C++/Python; Scientific Computing software libraries, Reduced Order
modelling techniques (reduced basis methods, POD), efficient
geometrical parametrisation techniques.

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From: Fabio Nobile [log in to unmask]
Date: October 21, 2020
Subject: Instructor Position, Applied/Computational Mathematics, EPFL

The Institute of Mathematics at the Ecole Polytechnique Federale de
Lausanne (EPFL) invites applications for a full-time instructorship in
Applied and/or Computational Mathematics.

The term of the position is two years, with the possibility of
extension for another two years.

Instructors are expected to teach Mathematics courses at all levels in
French or English, with an initial teaching load corresponding to half
the teaching load of regular faculty, and gradually progressing to the
latter. Moreover, instructors are expected to develop and sustain an
excellent independent research program. They are welcome to
collaborate and encouraged to interact with members of the Institute,
but they maintain full research independence.

EPFL salaries for instructors are highly competitive. In addition,
instructors receive a substantial yearly budget for travel expenses
and other expenditures.

Applications may be submitted by December 1st, 2020 at
https://recruiting.epfl.ch/Vacancies/1529/Description/2

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From: Xing Cai [log in to unmask]
Date: October 21, 2020
Subject: Research Scientist & Postdoc Positions, Simula Research Laboratory

The Department of High-Performance Computing, Simula Research
Laboratory, is currently having one open position of research
scientist and one open position of post-doc. The application deadline
is November 18.  For more info, please visit:
https://www.simula.no/about/job/high-performance-computing-call-research-scientist-and-
postdoc .


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From: Cassio Oishi [log in to unmask]
Date: October 21, 2020
Subject: Postdoc Position, Applied Mathematics

This proposal sets out a research plan to investigate a set of
adaptive data structures and computational methods when applied to
solve non- Newtonian materials in complex moving interface flows. This
project will focus on improvements on hybrid simulations, merging the
advantages of static adaptive grids and moving structures such as
particles to track the surface position in 3D. RBF-FD (Radial Basis
Function-Finite Difference) technique will be applied to particle
interpolations and differential values computation to combine both
techniques seamlessly. Moreover, applying high accurate boundary
conditions over the particles' surface allow for improved tracking of
the correct surface behavior.  The project is associated with the
Center for Mathematical Sciences Applied to Industry (CeMEAI) - a
Research, Innovation and Dissemination Center (CEPID) in the state of
Sao Paulo (Brazil) supported by FAPESP (Sao Paulo Research Foundation)
- and is hosted as by the Faculty of Science and Technology of the Sao
Paulo State University (FCT-UNESP) at Presidente Prudente.  Candidates
must hold a doctoral degree in Applied Mathematics, or a related area,
with experience in adaptive data structures and methods to numerically
solve fluid equations with a hybrid approach. To apply please email
(only PDF files) the following items at [log in to unmask] until
November, 20, 2020: 1. A letter of interest, containing full contact
information, year graduated and citizenship/immigration status,
concisely responding to the research emphases above; 2. A CV; 3. A
cover letter including names and contact information for 3 references
(no letters please). Indicate 'CEPID Postdoc' in the subject field.

This opportunity is open to candidates of any nationalities. The
selected candidate will receive a FAPESP's Post-Doctoral fellowship in
the amount of R$ 7,373.10 monthly and a research contingency fund,
equivalent to 15% of the annual value of the fellowship which should
be spent in items directly related to the research activity.

More information about the fellowship is at:
fapesp.br/oportunidades/3927.

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From: Markus Rampp [log in to unmask]
Date: October 26, 2020
Subject: Postdoc Position, HPC/NA, Max Planck Computing and Data
Facility, Germany

The Max Planck Computing and Data Facility (MPCDF) is looking for a
Computational Scientist or HPC application expert (m/f/d)

The successful candidate will work on the development and optimization
of scientific high-performance computing (HPC) simulation codes,
primarily in the field of classical molecular dynamics and soft matter
research, as pursued in the Polymer Theory department at the Max
Planck Institute for Polymer Research. A major focus will be on
preparing applications for the upcoming exascale supercomputer
architectures.

The applicant should hold a PhD in Physics, Computer Science, applied
Mathematics, or a similar subject. A strong background in scientific
software development (ideally with C++ and Python), familiarity with
common parallel programming models (like MPI, OpenMP, CUDA), and some
experience with large, distributed software projects and
high-performance computing are required. Experience with
particle-based molecular dynamics simulations is desirable. We offer
the opportunity to work on state-of-the-art numerical algorithms,
leading HPC codes and latest supercomputer technology and to maintain
close collaborations with leading computational scientists and method
developers.

The full-time position starts as soon as possible and is initially
limited for a maximum period of three years. Salary will be based on
experience according to the German TVoD. For detailed information
please visit http://www.mpcdf.mpg.de/about-mpcdf/career/jobs/

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From: Markus Rampp [log in to unmask]
Date: October 26, 2020
Subject: Postdoc Position, HPDA/AI, Max Planck Computing and Data
Facility, Germany

The Max Planck Computing and Data Facility (MPCDF) is looking for a
Data Scientist or Machine Learning expert (m/f/d).

The successful candidate will work on data-analytics projects,
especially in the fields of machine learning and deep learning. The
main focus will be on developing and optimizing machine-learning
solutions for high-performance computing (HPC) systems.  The applicant
should hold a PhD in Physics, applied Mathematics, Computer Science or
a similar subject and have a strong background in developing and
optimizing end-to-end machine learning solutions. Deep knowledge of at
least one of the software frameworks Tensorflow, Pytorch or Mxnet is
necessary. A solid background in Python, and at least one other HPC
programming language such as C++, C, or Fortran is
required. Familiarity with the concepts and applications of
distributed deep learning and the Apache Spark platform is
desirable. Experience in high-performance computing is considered a
major plus.

We offer the opportunity to work on cutting-edge high-performance
data-analytics projects at the interface of data science and
high-performance computing, in close collaboration with leading
machine-learning experts and domain scientists of various Max Planck
Institutes, e.g. in the areas of materials and bio sciences,
theoretical chemistry, polymer research, astrophysics, plasma physics,
and particle physics. The full time position starts as soon as
possible and is initially limited for a maximum period of three
years. Salary will be based on experience according to the German
TVoD.


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From: Recruitment BCAM [log in to unmask]
Date: October 21, 2020
Subject: Postdoc Position, Math, Comp, Exp Neuroscience, BCAM

IC2020_10_ Postdoctoral Fellowship in Mathematical, Computational and
Experimental Neuroscience

Postdoctoral Fellowship in Mathematical, Computational and
Experimental Neuroscience (MCEN).

The researcher will work in the MCEN team, a vibrant international
group aiming to explain how the brain processes and stores
information, how these are disrupted under pathological conditions and
develop novel technologies to treat neurodegenerative diseases. Main
activities: Perform modelling and data analysis on biological data;
Interact with experimentalists and mathematicians alike.

APPLY AT: http://www.bcamath.org/en/research/job/ic2020-10-postdoctoral-fellowship-in-
mathematical-computational-and-experimental-neuroscience
DEADLINE: 16th November, 2020, 14:00 SPAIN

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From: Recruitment BCAM [log in to unmask]
Date: October 22, 2020
Subject: Postdoc Position, Mathematical models for COVID-19, BCAM

IC2020_10_Postdoctoral Fellowship in Biomathematics at the
Mathematical and Theoretical Biology Group

Mathematical models for COVID-19 epidemiology: assessing risks and
control measures

APPLY AT: http://www.bcamath.org/en/research/job/ic2020-10-postdoctoral-fellowship-in-
biomathematics-at-the-mathematical-and-theoretical-biology-group
DEADLINE: 16TH NOVEMBER, 14:00 SPAIN


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From: Carsten Burstedde [log in to unmask]
Date: October 21, 2020
Subject: Postdoc Position, Scientific Computing, Bonn Univ

A two-year postdoc position is available at the Institute for
Numerical Simulation at the University of Bonn, Germany. The
postdoctoral researcher will be working in the group of Professor
Carsten Burstedde, with a primary focus on scalable algorithms for
adaptive mesh refinement.  The appointment will include technical
research as well as implementation in the ``p4est'' software.
Furthermore, numerical solver design and interfacing to fluid dynamics
community codes will be part of the job description.

Candidates are expected to have obtained a doctorate degree in applied
mathematics, scientific computing, or a closely related field. We
expect proficient experience in the development of scientific software
and require first-hand knowledge of the use of high performance
computing environments. With respect to the greater context of
interdisciplinary collaborative work, communication skills will play
an important role.

The appointment is planned for 2021 and 2022 subject to funding (which
will be decided upon shortly) and according to German standard full
salary rates.

Please submit a current CV, a cover letter outlining motivation and
prior experience and two references that may provide a letter of
support to [log in to unmask]

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From: Grey Ballard [log in to unmask]
Date: October 20, 2020
Subject: Postdoc Position, Tensor Computations, Wake Forest Univ

Description: The Department of Computer Science at Wake Forest
University invites applications for a postdoctoral research fellowship
beginning in July 2021.  The candidate will work primarily with
Prof. Grey Ballard (http://www.wfu.edu/~ballard) to design, implement,
and analyze efficient algorithms for tensor computations using
parallelization and/or randomization.  We are particularly interested
in scholars who have a strong background in numerical linear algebra,
numerical analysis, and/or parallel and high-performance computing.
The successful candidate will collaboratively prepare presentations
and papers for dissemination of results and help train graduate and
undergraduate student research assistants.  In addition to conducting
research, the fellow will teach one computer science course per year.
This is a one-year contract position with possible extensions up to
three years.

Qualifications: Candidates should have a PhD in computer science,
mathematics, statistics, or a closely related field, with a strong
background in numerical linear algebra, numerical analysis, and/or
parallel and high- performance computing and some familiarity with
tensor computations.

Application: Candidates should submit a cover letter explaining
interests and goals with respect to both research and teaching, a
complete CV, and 2-3 references that could provide a letter of
support. Contact Grey Ballard ([log in to unmask]) with questions and
upon formal application. For more details and to apply, see
http://tiny.cc/WFU-Postdoc.

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From: Vu Thai Luan [log in to unmask]
Date: October 25, 2020
Subject: PhD Position, Numerical Analysis, Mississippi State Univ

A Ph.D. position is available within a three-year NSF grant: "New
Advanced Time Integration Methods for Multiphysics Systems and
Applications".

Research Topics: Development of new advanced time integration methods
(Exponential Integrators and Multirate Integrators) for multiphysics
nonlinear PDEs and application models in meteorology (numerical
weather prediction), computational fluid dynamics, computational
biology, and visual computing.

The successful candidate will be working under the supervision of
Dr. Vu Thai Luan (PI of the project) in the Department of Mathematics
and Statistics, Mississippi State University (MSU). MSU, founded in
1878, is one of the R1 universities (classified at the highest
research activity level) in the US and is Mississippi's leading
research university. The student will also have the opportunity to
collaborate with multidisciplinary researchers from MSU, SMU, KAUST,
Environment Canada, and several national Labs in the US.

Applicants must hold a Bachelor's or Master's degree in Mathematics or
Computational/Applied Mathematics. A good knowledge of numerical
analysis and scientific computing is a plus.

More information and application instructions:
https://vuthailuan.com/open-position/


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From: Alberto Paganini [log in to unmask]
Date: October 26, 2020
Subject: PhD Position, Numerical Analysis, Univ Leicester

The University of Leicester invites applications for a fully funded
3.5-year PhD studentship to work on the project "Structural
optimization applied to space missions" under the supervision of Dr
Alberto Paganini and Prof Emmanuil Georgoulis.

This project lies at the interface of numerical analysis and
scientific computing. The project focuses on new discretization
approaches to structural optimization and their application to
satellite design.

The application deadline is 23 November 2020.

For informal inquiries, please contact Dr Alberto Paganini at
[log in to unmask]

For a full project description and application details, visit
https://www.findaphd.com/phds/project/structural-optimization-applied-to-space-
missions/?p124431

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From: Nick Polydorides [log in to unmask]
Date: October 24, 2020
Subject: PhD Positions, Data Science, Univ of Edinburgh

The Real-time Simulation & Computational Imaging Group at the School
of Engineering invites applications for PhD positions on randomised
numerical algebra for

(i) 'Real-time image restoration', and
(ii) 'Sketching for data-intensive health analytics'

The aim of these posts is to pursue research in the exciting new field
of randomised numerical algebra in order to expedite algorithms for
image restoration and online model learning.

Candidates should have an above-average master's/diploma degree in
mathematics, statistics or computer science with a focus on inverse
problems, Monte Carlo methods and linear algebra.

Further and eligibility please visit
http://www.homepages.ed.ac.uk/npolydor/PhD1_2021.pdf
http://www.homepages.ed.ac.uk/npolydor/PhD2_2021.pdf

More info on our group's activities and projects
http://www.homepages.ed.ac.uk/npolydor

Informal enquiries: [log in to unmask]
Deadline: 15th of January 2021.


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From: Antje Herbst [log in to unmask]
Date: October 22, 2020
Subject: Call for Papers, Reduced Order Modeling in Geosciences

GEM - International Journal on Geomathematics publishes papers which
describe, model and map the complexity of the processes within the
Earth, at its surface, and in the atmosphere by means of modern
mathematical methodologies.

GEM has established Topical Collections to highlight important topics
in the journal. The Topical Collection on recent advances in "Reduced
Order Modeling in Geosciences" edited by Bulent Karasozen provides an
overview of the progress in this rapidly developing area, to identify
current challenges, and to present and discuss new approaches. The
topics covered include but are not limited to geophysical flows,
seismic inversion, poroelasticity, fracture modeling, reservoir
simulations, geomechanics, and data-driven model reduction.

In addition, submissions of overview papers reporting on significant
progress in the field are highly encouraged. The guest editor of this
Topical Collection invites interested authors to submit their
contributions to GEM (https://www.springer.com/journal/13137/)
starting September 1, 2020 until January 31, 2021 and to spread this
"Call for Papers" to other colleagues active in this area.

Click the link below to download the PDF with all information:
https://resource-cms.springernature.com/springer-cms/rest/v1/content/18261530/data/v1


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From: Oleg Burdakov [log in to unmask]
Date: October 20, 2020
Subject: Contents, Special Issue, OMS, 60th Birthday of Ya-xiang Yuan

Optimization Methods & Software (OMS)
special issue dedicated to the 60th birthday of Ya-xiang Yuan

OMS 35(2), Part I:
https://www.tandfonline.com/toc/goms20/35/2

Yu-Hong Dai, Xin Liu, Jiawang Nie and Zaiwen Wen, Preface

Azam Asl and Michael L. Overton, Analysis of the gradient method with
an Armijo-Wolfe line search on a class of nonsmooth convex functions

C. Cartis, N.I.M. Gould and Ph.L. Toint, A concise second-order
complexity analysis for unconstrained optimization using high-order
regularized models

Wenbo Gao, Donald Goldfarb and Frank E. Curtis, ADMM for Multiaffine
Constrained Optimization

Nicholas I.M. Gould and Valeria Simoncini, Error estimates for
iterative algorithms for minimizing regularized quadratic subproblems

Jiawang Nie, Liu Yang and Suhan Zhong, Stochastic Polynomial
Optimization

Dingtao Peng and Xiaojun Chen, Computation of second-order directional
stationary points for group sparse optimization

Xin Zhang, Qin Ni and Zhili Ge, A convergent Newton algorithm for
computing Z-eigenvalues of an almost nonnegative irreducible tensor

Xuezhong Wang, Maolin Che, Liqun Qi, Yimin Wei, Modified gradient
dynamic approach to the tensor complementarity problem

Leqin Wu, Xin Liu and Zaiwen Wen, Symmetric rank-1 approximation of
symmetric high-order tensors

OMS 35(4), Part II:
https://www.tandfonline.com/toc/goms20/35/4

Albert S. Berahas, Raghu Bollapragada and Jorge Nocedal, An
Investigation of Newton-sketch and subsampled Newton methods

Yakui Huang, Yu-Hong Dai, Xin-Wei Liu and Hongchao Zhang, Gradient
methods exploiting spectral properties

Zeyu Jia, Zaiwen Wen and Yinyu Ye, Toward Solving 2-TBSG Efficiently

Jian Sun, Dachuan Xu, Deren Han, Wenjing Hou and Xiaoyan Zhang,
Randomized mechanism design for decentralized network scheduling

Conghui Tan, Yuqiu Qian, Shiqian Ma and Tong Zhang, Accelerated
dual-averaging primal-dual method for composite convex minimization

Haiyan Wang and Jinyan Fan, Convergence rate of the
Levenberg-Marquardt method under Holderian local error bound

Li Wang, Lei-hong Zhang, Zhaojun Bai and Ren-Cang Li, Orthogonal
canonical correlation analysis and applications

Xiao Wang and Hongchao Zhang, Inexact proximal stochastic second-order
methods for nonconvex composite optimization

Jialiang Xua and Yun-Bin Zhao, Stability analysis for a class of
sparse optimization problems

Yinqiao Yan and Qingna Li, An efficient augmented Lagrangian method
for support vector machine dedicated to Professor Ya-xiang Yuan on the
occasion of his 60th birthday,

OMS 35(5), Part III:
https://www.tandfonline.com/toc/goms20/35/5

E.G. Birgin and J.M. Martinez, Complexity and performance of an
augmented Lagrangian algorithm

Tamir Hazan, Shoham Sabach and Sergey Voldman, Stochastic proximal
linear method for structured non-convex problems

Florian Jarre, Yu-Hong Dai and Felix Lieder, On the existence of
affine invariant descent directions

Wei Peng, Yu-Hong Dai, Hui Zhang and Lizhi Cheng, Training GANs with
centripetal acceleration

Yuki Satake, Tomohiro Sogabe, Tomoya Kemmochi and Shao-Liang Zhang, On
a transformation of the *-congruence Sylvester equation for the least
squares optimization

Cong Sun and Yanfei Wang, Gravity-magnetic cross-gradient joint
inversion by the cyclic gradient method

Xiaojiao Tong, Liu Yang, Xiao Luo and Bo Rao, A stochastic dual
dynamic programming method for two-stage distributionally robust
optimization problems

Yule Zhang, Jia Wu and Liwei Zhang, The rate of convergence of
proximal method of multipliers for nonlinear programming


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