NA Digest, V. 22, # 36

NA Digest Monday, October 31, 2022 Volume 22 : Issue 36


Today's Editor:

Daniel M. Dunlavy
Sandia National Labs
dmdunla@sandia.gov

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From: Peter Rentrop peter-rentrop@t-online.de
Date: October 31, 2022
Subject: Roland Bulirsch (1932-2022)


With sadness we have to inform you that Roland Bulirsch (1932-2022)
passed away on 21 September 2022. He followed his beloved wife
Waltraut who died in 2020. Born 10 November 1932 to working-class
parents in Reichenberg (Bohemia), he experienced occupation, war and
expulsion. From 1947 till 1951 he received a professional training as
an engine fitter at Siemens-Schuckert (Nuremberg) and worked there
afterwards as a machinist. In 1954 he finished high school and began
studying mathematics and physics at the Technische Hochschule in
Munich, graduating in 1959. Here he earned a mathematics Ph.D. in
1961 and the habilitation in mathematics in 1965. During his time in
Munich the famous extrapolation algorithms result from a joint
research with J. Stoer. In 1967 he became Associate Professor at the
University of California, San Diego, which appointed him Full
Professor in 1968. Here he developed the multiple shooting algorithm
with applications to space problems as well as arithmetic-geometric
means in elliptic integrals. In 1969 he went to the University of
Cologne as Full Professor, in 1972 he accepted a full professorship at
the Department of Mathematics of the TU Munchen and remained there
until his retirement in 2001.

He was an excellent and inspiring teacher and an enthusiastic
researcher; more than 200 diploma theses, 40 Ph.D. theses and 12 venia
legend theses are witnesses of his enourmous influence. R. Bulirsch
embodied the ideal of a mathematician: He could explain even the most
complicated things simply. He was the author (with J. Stoer) of
Introduction to Numerical Analysis, a standard reference for the
theory of numerical methods. He served as an editor for many
journals. He was a member of the TUM Senate and twice Dean of the
Department of Mathematics For more than a decade he was a referee for
the German Science Foundation and headed the committee for Mathematics
from 1984-1988. R. Bulirsch was always open to political and cultural
questions. He was an expert in orchids, had a deep connection to music
and was highly interested in literature, art and astronomy. We mourn
with his two daughters and his grandchildren.

R. Callies, P. Rentrop, TU Munchen


From: Tzanio Kolev tzanio@llnl.gov
Date: October 23, 2022
Subject: MFEM Version 4.5


Version 4.5 of MFEM, a lightweight, general, scalable C++ library for
finite element methods, is now available at: https://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.

Some of the new additions in version 4.5 are:
- MFEM Docker container and cloud support.
- New and improved integrations with Enzyme, Algoim, Moonolith, hypre.
- Efficient GPU kernels for LOR matrix assembly and DG mass inversion.
- Full assembly and device support for LinearForm integrators.
- Partial assembly and matrix-free operators on mixed meshes.
- New miniapp for automatic differentiation of nonlinear elasticity.
- Improved mesh optimization and physical space interpolation.
- Support for submesh extraction.
- New fractional PDE example.

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, derefinement 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 a
BSD license. For more details, see the interactive documentation and
the full CHANGELOG at https://github.com/mfem/mfem.


From: Sarah Leigh Lederer sarah-leigh.lederer@plus.ac.at
Date: October 28, 2022
Subject: Berlin Workshop on Numerical Analysis, Germany, Nov 2022


The Berlin Workshop on Numerical Analysis 2022 is being held from
November 1st to November 22nd, 2022
Rudower Chausee 25, Campus Adlershof, Berlin

The aim of the workshop is to discuss recent developments in numerical
analysis. The topics cover, for instance, error control and
adaptivity, non- standard finite elements (ranging from classical
non-conforming methods to neural networks). The workshop extends over
three weeks and is intended to create a stimulating and relaxed
atmosphere to discuss topics in numerical analysis, initiate new
projects and advance existing projects. A maximum of one or two
lectures per day on average are planned.

The Berlin Workshop on Numerical Analysis is organised by Andreas
Schroder (PLU Salzburg) and Carsten Carstensen (HU Berlin).

There is no registration necessary. For any questions concerning the
workshop please send an email to: graesslb@math.hu-berlin.de

Further information can be found at:
https://www2.mathematik.hu-berlin.de/~ccafm/bwna2022/index.html


From: Emmanuil Georgoulis E.Georgoulis@hw.ac.uk
Date: October 26, 2022
Subject: One World Numerical Analysis Series, ONLINE, Nov 2022


The One World Numerical Analysis Series is continuing this academic
year. The series will now be hosted by Augsburg University and will
(typically) run fortnightly on Mondays via the Zoom platform.
Attendance is open, but requires a basic initial registration via the
OW-NA Series webpage:
https://www.uni-augsburg.de/en/fakultaet/mntf/math/prof/numa/one-world-numerical-analysis-seminar/

(Upon registration, you will be receiving a link to the seminars, near
the seminar time.)

The (typical) time for the seminars is 2pm British Summer Time (BST),
3pm Central European Summer Time (CEST), 9pm Beijing, 9am New York.

The first scheduled seminars are:

1) 07.11.2022 Gabriel Barrenechea, University of Strathclyde, UK.
Title: The discrete maximum principle, and positivity preservation, in
finite element methods.

2) 21.11.2022 Jens Markus Melenk, Vienna University of Technology,
Austria. Title: hp-FEM for fractional diffusion.

We look forward to your participation.

The organisers:
Lehel Banjai, Heriot-Watt University
Emmanuil Georgoulis, Heriot-Watt University/NTU Athens
Maria Lopez Fernandez, University of Malaga
Charalambos Makridakis, IACM/University of Sussex/Crete
Daniel Peterseim, University of Augsburg


From: Jan Martin Nordbotten jan.nordbotten@uib.no
Date: October 30, 2022
Subject: SIAM Geosciences (GS23), Norway, Jun 2023


The deadline for submission of Minisymposia for the 2023 edition of
the SIAM Conference on Mathematical and Computational Issue in the
Geosciences (SIAMGS23) is approaching. The conference will take place
in Bergen, Norway, on June 19-22 2023.

The deadline is the 21st of November 2022. Further information is
available on https://www.siam.org/conferences/cm/conference/gs23.


From: Tommaso Giovannelli tommaso.giovannelli@gmail.com
Date: October 23, 2022
Subject: Modeling and Optimization (MOPTA), USA, Aug 2023


The Industrial and Systems Engineering (ISE) Department at Lehigh
University is excited to host the Modeling and Optimization: Theory
and Applications (MOPTA) 2023 Conference, which will take place at
Lehigh University in Bethlehem, Pennsylvania, USA on August 16-18,
2023.

MOPTA conferences bring together a diverse group of researchers from
both discrete and continuous optimization, working on both theoretical
and applied aspects. There will be invited plenary talks from
distinguished speakers as well as organized sessions and contributed
talks, spread over three days. Our goal is to present a diverse set of
exciting new developments from different optimization areas while at
the same time providing a setting that will allow increased
interaction among the participants. Information about important
deadlines and the 15th AIMMS- MOPTA Optimization Modeling Competition
will be made available later this year.

The list of distinguished plenary speakers who have already confirmed
their participation includes Laura Albert (University of
Wisconsin-Madison), Omar Ghattas (University of Texas at Austin),
Fatma Kilinc-Karzan (Carnegie Mellon University), Xiaodi Wu
(University of Maryland), and Wotao Yin (Alibaba Group US).

For more information, please visit
https://coral.ise.lehigh.edu/~mopta/.


From: Andrei Draganescu draga@umbc.edu
Date: October 26, 2022
Subject: Tenure-Track Position, Applied Mathematics, UMBC


The Department of Mathematics of Statistics at the University of
Maryland, Baltimore County (UMBC) has an opening for a tenure track
faculty position in Applied Mathematics, starting from August
2023. The appointment is for 9 months per year. Candidates should have
finished their PhD in applied mathematics (or related fields) before
their appointment's start date, and show promise for a career in
research and teaching. A successful candidate should have a strong
background in applied and/or computational mathematics, possess
research synergy with current faculty members, and teach courses in
the Department of Mathematics and Statistics, UMBC.

For more information please visit
https://mathstat.umbc.edu/tenure-track-position-in-applied-mathematics/.


From: Grady Wright gradywright@boisestate.edu
Date: October 28, 2022
Subject: Tenure-Track Position, Data Science, Boise State Univ


The Department of Mathematics at Boise State University invites
applications for a tenure-track position in data science (broadly
interpreted) at the rank of assistant professor starting in fall
2023. Applicants should have strong research potential in statistical
computing, optimization, numerical linear algebra, or mathematical
foundations of data science or machine learning. Particular interest
is in applicants with interdisciplinary connections to data-driven
applications, especially those involving the environment.

Boise State's innovative transdisciplinary approach to research and
education has driven its meteoric rise to an R2 university. The
Mathematics Department is a leader in data science efforts at both the
undergraduate and graduate levels and is an essential contributor to
the new School of the Environment (SoE).

Boise State is located in Idaho's capital city and largest
metropolitan area, which serves as the government, business,
high-tech, economic, and cultural center of the state. Boise offers a
great quality of life: a family friendly culture, a vibrant downtown,
and great outdoor recreation activities. To further enhance the
quality of life Boise offers, the university has committed to
sustaining the conditions necessary for faculty to enter and thrive in
their academic careers while meeting personal and family
responsibilities.

For more details on the position and to apply see
https://www.mathjobs.org/jobs/list/21283. Applications received by
December 7, 2022 will be given full consideration.


From: Giordano Tierra gtierra@unt.edu
Date: October 25, 2022
Subject: Tenure-Track Position, NA & PDEs, Univ of North Texas


The Department of Mathematics at the University of North Texas (UNT),
Denton, invites applications for a tenure-track Assistant Professor
position in numerical analysis, applied partial differential equations
or a closely related field.

The successful candidate must have a Ph.D. in Mathematics or in
Applied Mathematics. Applications will be accepted until the position
is filled. To guarantee full consideration, the application should be
received by November 15, 2022.

In order to be considered for the position, applications should be
submitted to the UNT website:
https://jobs.untsystem.edu/postings/64695

More information about the position and UNT can be found in the ad at
Mathjobs: https://www.mathjobs.org/jobs/list/21168


From: Edmond Chow echow@cc.gatech.edu
Date: October 25, 2022
Subject: Tenure-Track Positions, CSE, Georgia Tech


The School of Computational Science and Engineering (CSE) at the
Georgia Institute of Technology in Atlanta, Georgia, USA, invites
applications for multiple openings for the position of Assistant
Professor (tenure-track); openings for Associate Professor and
Professor (tenured or tenure-track) are also available. CSE focuses
on foundational research of an interdisciplinary nature that enables
advances in science, engineering, medical, and social domains.

Duties of these positions include developing and sustaining a research
program in one or more of our core areas: high-performance computing,
scientific and numerical computing, modeling and simulation, discrete
algorithms, and data analytics (including machine learning and
artificial intelligence). Duties also include teaching undergraduate
and graduate courses (classroom teaching), as well as providing
service to the School, College and the Institute. A PhD degree is
required by the starting date of the job, in a discipline relevant to
the field of Computational Science and Engineering, including a degree
in Computer Science, Mathematics, Engineering, or Science.

For information on how to apply, go to:
https://cse.gatech.edu/content/faculty-hiring/. Questions can be sent
to CSE-recruiting@cc.gatech.edu. For full consideration, applications
are due by December 1, 2022.


From: Rodrigo B Platte rplatte@asu.edu
Date: October 26, 2022
Subject: Assistant/Associate Professor Position, Arizona State Univ, USA


The School of Mathematical and Statistical Sciences (SoMSS) at Arizona
State University invites applications for a full-time tenure-eligible
position in applied and computational mathematics at the rank of
Assistant or Associate Professor. Anticipated start date is August 16,
2023. The Applied and Computational Mathematics program consists
approximately of 20 faculty members and has close ties with our
statistics and theoretical math groups.

The essential duties of the position will be to conduct research on
areas of applied mathematics, computational mathematics, optimization,
and/or data science, publish in appropriate high-quality journals,
disseminate research at conferences and colloquia, provide quality
teaching and mentoring in our undergraduate and graduate programs, and
participate in appropriate professional service.

Required Qualifications: " A Ph.D. in mathematics, applied
mathematics, optimization, statistics, or a closely related area by
the time of appointment. " Demonstrated potential for excellence in
research and teaching, relative to career level. " Demonstrated
understanding of the importance of diversity, equity, and
inclusiveness in the mathematical community.

Desired Qualifications " Documented record of published research in
the areas of applied mathematics, computational mathematics,
optimization, and/or data science. " Established record or strong
potential for grant support, relative to career level. " Demonstrated
experience and/or interest in teaching and mentoring. " Documented
experiences and/or expertise indicative of strong support for
individuals who have been systemically underserved in the mathematical
sciences.

To apply, submit the following through Mathjobs at
https://www.mathjobs.org/

The application deadline is 4:00 pm Arizona time on November 20, 2022
only applications that are complete by the deadline will be
considered. If the position is not filled, remaining applications will
be considered every two weeks thereafter until the search is closed.


From: Konstantinos Zygalakis k.zygalakis@ed.ac.uk
Date: October 26, 2022
Subject: Chancellor Fellowship Positions, Mathematics, Univ of Edinburgh


The School of Mathematics of the University of Edinburgh invites
applications for Chancellor's Fellowships. These are 5-year tenure
track fellowships designed to provide talented early career
researchers with the support required to develop into leading
research-active academics. We strongly welcome applicants whose
research centers on
- mathematics of data,
- applications of mathematics to healthcare,
- sustainability and climate change.

See https://bit.ly/3VPBEKi for details. Applications close at 5 pm
(UK) on 28th November 2022.


From: Doug Arnold arnold@umn.edu
Date: October 24, 2022
Subject: Postdoc Position, Computational Science and Math, Univ Minnesota


The School of Mathematics at the University of Minnesota invites
applications for two post-doctoral positions in computational science
and mathematics under the direction of Doug Arnold. The postdocs will
join the celebrated Simons Collaboration on the Localization of Waves
(https://cse.umn.edu/wave/), an international group of leading
mathematicians and physicists working together on some of the most
compelling puzzles in modern condensed matter physics. Computational
simulations are a major enabling tool in this work, and the
post-doctoral positions are to advance the collaboration through the
design, implementation, visualization, and analysis of
state-of-the-art numerical methods for solving large scale systems of
partial differential equations and exploring their spectrum. We thus
seek a candidate with a strong background in numerical PDE. Prior
experience with the finite element method, eigenvalue problems, wave
propagation, quantum mechanics, and high performance computing are all
desirable. Salary will be commensurate with qualifications and
experience and there will be a generous allowance for travel. The
preferred starting date is late August 2023, or sooner, and the
duration is two years, with a third year possible depending on funding
and performance.

Applications should be submitted through Mathjobs at
https://www.mathjobs.org/jobs/list/20678

They will be reviewed starting December 1, 2022, continuing until the
position is filled. Contact Doug Arnold (arnold@umn.edu) with
questions.

The University of Minnesota is an Equal Opportunity Educator and
Employer.


From: Emil Constantinescu emconsta@mcs.anl.gov
Date: October 27, 2022
Subject: Postdoc Position, Computational Statistics, Probability, ML, Argonne


We seek a postdoctoral candidate with a strong background in
computational statistics and uncertainty quantification to develop
robust and effective algorithms for solving stochastic inverse
problems in quantum chromodynamics and nuclear tomography.

The incumbent will be part of a large team of applied mathematicians,
statisticians, computational scientists, and nuclear physicists under
the QuantOm collaboration project:
https://www.anl.gov/phy/quantom. The work involves sample-based
probability distribution learning and spans computational statistics,
machine learning, uncertainty quantification, and numerical analysis.

Position Requirements: Recent or soon-to-be completed Ph.D. (typically
completed within the last 0-3 years) in statistics, probability,
applied mathematics, or another scientific or engineering field with a
strong emphasis on solving inverse problems and uncertainty
quantification.; practical verbal and written communication skills; a
mixture of experience and interest in learning the following topics:
Inference-based computational statistics: Bayesian & likelihood
methods, high dimensional sampling, computational and variational
inverse problems, dimension reduction and statistical analysis of
high-dimensional datasets. Other desired but not required knowledge
include statistical testing, goodness-of-fit tests, probability
coverage, ML with a strong emphasis on variational, probabilistic and
statistical ML approaches, normalizing flows, generative modeling,
Optimal transport, and distance metrics. Python code development and
devops, such as git and CI/CD, are a plus.

Applications and a detailed description, including qualifications for
different research tracks, are found at
[https://tinyurl.com/bdee2aej].


From: SA Mohammadi abbasalimath@gmail.com
Date: October 31, 2022
Subject: Postdoc Position, PDE-Constrained Optimization, Wits Univ


A full-time postdoctoral research fellowship is available in the area
of PDE-Constrained Optimization Problems at the University of the
Witwatersrand, South Africa. The fellowship will enable an outstanding
doctoral graduate to obtain additional experience in research and
innovation. We are specifically looking for an applicant that is
working in PDEs, preferably with a specialization in PDE-Constrained
Optimization Problems. Depending on the candidate's productivity, the
fellowship may be renewed for a few additional years beyond its
initial one-year term.

ELIGIBILITY CRITERIA: Must have graduated within the last five years
with a PhD degree in Mathematics with a specialization in PDEs,
preferably specialized in PDE-Constrained Optimization Problems. Must
have a proven track record in research with at least two papers
(published or accepted) and preferable already some international
network. Successful applicants must be able to relocate to the
University of the Witwatersrand for the duration of the fellowship.

THE SUCCESSFUL CANDIDATE WILL BE REQUIRED TO: Demonstrate relevant
experience, understanding and knowledge of PDEs and Optimization.
Conduct innovative research in in PDE-Constrained Optimization
Problems. Maintain publishing in high quality journals and present
work at national and international conferences. Contribute to the
research productivity of the school and assist in research endeavours
of it, including the organization of workshops and supervision of
postgraduate students.

COMMENCEMENT OF FELLOWSHIP: As soon as possible.

APPLICATION: Please email the following documents to Prof S.A.
Mohammadi by email: abbas.mohammadi@wits.ac.za . Full CV including a
list of research publications. Full transcript of recent academic
records and copy of doctoral degree certificate and any other relevant
certificate. Copy of ID document (or copy of passport in the case of
foreign applicants)

CLOSING DATE: 31 December 2022
FOR ENQUIRES: abbas.mohammadi@wits.ac.za


From: Rodrigo B Platte rplatte@asu.edu
Date: October 27, 2022
Subject: Postdoc Positions, Arizona State Univ


The School of Mathematical and Statistical Sciences (SoMSS) at Arizona
State University invites applications for Postdoctoral Research
Scholar positions. The anticipated start date is August 16,
2023. These full-time academic-year, benefits-eligible positions are
renewable on an annual basis through spring 2026 contingent upon
satisfactory performance, availability of resources, and the needs of
the university. The essential duties of the position will be to
conduct research in the mathematical sciences, along with a teaching
load that is normally three courses per year.

Required Qualifications: A Ph.D. in the mathematical or statistical
sciences, or a closely related area by the time of appointment.
Applicants must be within five years of receipt of their PhD to be
considered for initial appointments and subsequent renewals.
Demonstrated potential for excellence in research and teaching.

Desired Qualifications: A documented research record in an area that
meshes with the research interests of a current faculty member or
group of faculty members (SoMSS has strong research groups in
analysis, combinatorics, computational mathematics, differential
equations, dynamical systems, geometry, graph theory, mathematical
biology, mathematics education, number theory, probability, and
statistics). Demonstrated success working with diverse student and/or
faculty populations.

The application is through Mathjobs:
https://www.mathjobs.org/jobs/list/21206

The application deadline is 4:00 pm Arizona time on December 2, 2022;
only applications that are complete by the deadline will be given full
consideration. Applications will continue to be accepted on a rolling
basis for a reserve pool after the deadline. Applications in the
reserve pool may then be reviewed in the order in which they were
received until the position is filled.


From: Martin Kronbichler martin.kronbichler@uni-a.de
Date: October 28, 2022
Subject: Postdoc/PhD Positions, PDE Solvers for Exascale Computers


The project "PDExa: Optimized software methods for solving partial
differential equations on exascale supercomputers" strives to develop
new classes of algorithms and implementations for the efficient
solution of partial differential equations on exascale hardware. The
discretization methods involve continuous and discontinuous finite
element methods in a variety of applications, including fluid dynamics
and physics. The project is a collaborative effort between five PIs at
four Universities in Germany, namely in Augsburg, Bochum, Karlsruhe
and Munich. We are currently looking for applications for PhD or
PostDoc positions.

More information can be found at:
https://www.uni-augsburg.de/de/fakultaet/mntf/math/prof/hpc/pdexa/positions


From: Vyacheslav Kungurtsev vyacheslav.kungurtsev@fel.cvut.cz
Date: October 24, 2022
Subject: PhD Position, Causal AI for Public Health


Structured Graphical Models for Causal Inference is an increasingly
important class of Machine Learning techniques, especially in
applications of public health and medicine. Using careful
well-principled structure in the modeling, conclusions can be reached
regarding the cause-effect, rather than simply correlational
influence, with far reaching implications for understanding and
treatment/policy. The development, analysis, training and inference
of these models is highly nontrivial, and involves an array of tools
from statistics and information theory along with optimization and
numerical analysis. As part of a Horizon Europe EU-wide project, we
are seeking motivated and competent PhD students to pursue research in
the associated fields. As part of this position, we seek a PhD
student with a background in computer science, statistics, and/or
applied mathematics to work on probabilistic graphical models subject
to potentially time varying trends and exhibiting potential for causal
inference. The project will involve developing new models, proving
statistical properties thereof, developing techniques to adequately
train them with strong accuracy and generalization, and testing them
on real biomedical and public health data. The PhD student will be
supervised jointly by Vyacheslav Kunurtsev and Ondrej Kuzelka at the
Czech Technical University in Prague, the Department of Computer
Science. A preference is given to candidates with experience in
programming, especially (but not limited to) Python.

We expect to start interviewing candidates as soon as possible, with a
view of a start between January and September 2023. Please write
vyacheslav.kungurtsev@fel.cvut.cz


From: Kirk M. Soodhalter ksoodha@maths.tcd.ie
Date: October 25, 2022
Subject: PhD Position, High Performance Computing, Ireland


We are advertising an open PhD position at Trinity College Dublin. It
is part of our IBM-TCD PhD Fellowship in High Performance Computing
cooperation with IBM. The project title is "Error Mitigation & Circuit
optimisation for Quantum Time Evolution - theory and algorithms".

The School of Mathematics at Trinity College Dublin and IBM Research
Dublin invite applications for a jointly supervised, fully funded PhD
position. The PhD project will concern applying techniques from
numerical analysis and numerical PDEs to address numerical challenges
arising in quantum computing, namely estimation and optimization of
errors arising in quantum time evolution.

Further details and information for interested applicants can be found
at https://www.maths.tcd.ie/~ksoodha/jobs/IBM-TCD-Announcement.pdf.
This is an attractive position for prospective students, in terms of
remuneration, experience working with academic and private sector
collaborators on an interesting topic, and job opportunities after the
PhD is completed.

For further information please contact me (ksoodha@maths.tcd.ie) at
Trinity College Dublin or Sergiy Zhuk (sergiy.zhuk@ie.ibm.com) at IBM
Research Dublin.

For consideration for the position please submit a full CV including
the names of 3 potential referees to me (ksoodha@maths.tcd.ie).



From: Chen Huang chuang3@fsu.edu
Date: October 26, 2022
Subject: PhD Positions, Computational Science, Florida State Univ


The Department of Scientific Computing at Florida State University
welcomes applicants to apply for our interdisciplinary Ph.D. program
in computational science. Students from all branches of science,
mathematics, and engineering are encouraged to apply. Our department
lies at the intersection of applied mathematics, science, and
engineering, and has the unique opportunity to train students in areas
that cut across disciplines. We work on a wide range of topics in
computational sciences, including computational mathematics,
computational fluid dynamics, computational astrophysics,
computational biology, computational materials science, computational
oceanography, and machine learning.

Admission requirements: A bachelor's degree in any field of science,
mathematics, and engineering. A minimum 3.0 GPA on a 4.0 scale in all
coursework attempted while registered as an upper-division
undergraduate student. Graduate record examinations (GRE) general
test: 85% or above in quantitative and 50% or above in verbal.
Language: A native English speaker or pass the TOEFL test
(international applicants only).

To know more about various research areas at our department, please
visit: https://www.sc.fsu.edu/research/faculty

For application, please visit: https://www.sc.fsu.edu/graduate/phd

If you have any questions, please contact: chuang3@fsu.edu


From: Hossein Gorji mohammadhossein.gorji@empa.ch
Date: October 31, 2022
Subject: PhD Positions, Model-Data Fusion, Empa, Switzerland


Empa is the research institute for materials science and technology of
the ETH Domain and conducts cutting-edge research for the benefit of
industry and the well-being of society. The Laboratory of Multiscale
Studies in Building Physic in Dubendorf, Switzerland invites
applications for two PhD students for Model-Data Fusion on Complex
Networks for a 4 year-project.
https://www.empa.ch/en/web/empa/multiscale-studies-in-building-physics

The doctoral researchers will focus on the development of stochastic
and data-driven methodologies to improve model predictivity and guide
intervention measures on multiscale networks. In particular, the
applications will deal with disease spread in human populations and
cascade failure in power networks. The project will tackle fundamental
challenges arising from modeling large-scale networks and integrate
original ideas across machine learning and stochastic modeling to
enable efficient yet high-fidelity predictions of complex network
dynamics. We are looking for two PhD students with strong analytical
background, and MSc degree in Engineering, Applied Mathematics,
Physics, or a related field. Professional command of English (both
written and spoken) is mandatory. The successful candidates show
enthusiasm for conducting original research and strives for scientific
excellence. Prior exposure to stochastic models, machine learning, or
network science would be highly desirable.

For more details on the position and application procedures, please
check out the original job advertisement on:
https://apply.refline.ch/673276/1651/pub/1/index.html


From: Ursula Tian ursula.tian@mdpi.com
Date: October 23, 2022
Subject: CFP, AppliedMath, Special Issue


In this Special Issue, we invite manuscripts dealing with theoretical
and application results with consistent methods for the estimation of
expectations, nonlinear functions of expectations, quantiles, and
other performance measures from the output of simulation experiments.
Applications and results for both transient and steady-state
simulations will be considered, and methodologies that consider the
assessment of the accuracy of the corresponding point estimators are
especially welcome. Works related to numerical approaching theory and
computer simulation with direct applications in physics such as fluid
flow, heat and mass transfer, mechanics, industrial processing
analysis based on simulation are also welcome.

More information can be found at:
https://www.mdpi.com/journal/appliedmath/special_issues/554QNHWEH9

We can provide 100% discounts on APC. If you are interested, please
contact the AppliedMath Editorial Office (appliedmath@mdpi.com), or
the leading Guest Editor, Prof. Dr. David F. Munoz (davidm@itam.mx).


From: Alex Barnett abarnett@flatironinstitute.org
Date: October 29, 2022
Subject: Contents, Advances in Computational Mathematics, 48 (5)


Advances in Computational Mathematics. Volume 48, Issue 5.
https://link.springer.com/journal/10444/volumes-and-issues/48-5

CONTENTS

Error estimates of H(div)-conforming method for nonstationary
magnetohydrodynamic system. Qianqian Ding, Shipeng Mao, Jiaao Sun

Numerical analysis for two-phase flow with non-equilibrium capillary
pressure in anisotropic porous media. Khaled Bouadjila, Ali Samir
Saad, Mazen Saad, Wissal Mesfar

Optimized Ventcel-Schwarz methods for the Cahn-Hilliard equation
discretized by the stabilized linear Crank-Nicolson scheme. Yafei
Sun, Yingxiang Xu, Shuangbin Wang, Shan Gao

H-matrix approximability of inverses of FEM matrices for the time-
harmonic Maxwell equations. Markus Faustmann, Jens Markus Melenk,
Maryam Parvizi

Efficient function approximation on general bounded domains using
splines on a Cartesian grid. Vincent Coppe, Daan Huybrechs

Two-grid hp-version discontinuous Galerkin finite element methods for
quasilinear elliptic PDEs on agglomerated coarse meshes. Scott
Congreve, Paul Houston

Efficient randomized tensor-based algorithms for function
approximation and low-rank kernel interactions. Arvind K. Saibaba,
Rachel Minster, Misha E. Kilmer

Numerical investigation of two second-order, stabilized SAV ensemble
methods for the Navier-Stokes equations. Nan Jiang, Huanhuan Yang

Hermite interpolation by planar cubic-like ATPH. Thierry Bay,
Isabelle Cattiaux-Huillard, Laura Saini

Polycircular domains, numerical conformal mappings, and moduli of
quadrilaterals. Mohamed Nasser, Oona Rainio, Antti Rasila, Matti
Vuorinen, Terry Wallace, Hang Yu, Xiaohui Zhang.

Corrected trapezoidal rule for near-singular integrals in
axi-symmetric Stokes flow. Monika Nitsche

A fast direct solver for integral equations on locally refined
boundary discretizations and its application to multiphase flow
simulations. Yabin Zhang, Adrianna Gillman, Shravan Veerapaneni

An inertial extragradient algorithm for equilibrium and generalized
split null point problems. Yasir Arfat, Poom Kumam, Muhammad Aqeel
Ahmad Khan, Parinya Sa Ngiamsunthorn

Weak approximation of SDEs for tempered distributions and
applications. Yuga Iguchi, Toshihiro Yamada

Interpolation of 3D data streams with C^2 PH quintic splines.
Carlotta Giannelli, Lorenzo Sacco, Alessandra Sestini

Quadrature by fundamental solutions: kernel-independent layer
potential evaluation for large collections of simple objects. David
B. Stein, Alex H. Barnett

Convergence of consistent and inconsistent schemes for fractional
diffusion problems with boundaries. Ercilia Sousa


From: Irena Lasiecka lasiecka@memphis.edu
Date: October 25, 2022
Subject: Contents, Evolution Equations and Control Theory, 12 (1)


Contents- EECT-vol 12, nr 1.
https://www.aimsciences.org/eect

1.Controllability for Schrodinger type system with mixed dispersion on
compact star graphs, Roberto de A. Capistrano-Filho, Marcio Cavalcante
and Fernando A. Gallego

2.Stability properties for a problem of light scattering in a
dispersive metallic domain, Serge Nicaise and Claire Scheid

3.Mathematical analysis of an abstract model and its applications to
structured populations (I), Mohamed Boulanouar

4.On the effect of perturbations in first-order optimization methods
with inertia and Hessian driven damping, Hedy Attouch, Jalal Fadili
and Vyacheslav Kungurtsev

5.Optimal control for stochastic differential equations and related
Kolmogorov equations, Stefana-Lucia Anica

6.Stability of a damped wave equation on an infinite star-shaped
network, Ahmed Bchatnia and Amina Boukhatem

7.Asymptotic behavior of the wave equation with nonlocal weak damping,
anti-damping and critical nonlinearity, Chunyan Zhao, Chengkui Zhong
and Zhijun Tang

8.A general decay result for the Cauchy problem of plate equations
with memory, Salim A. Messaoudi and Ilyes Lacheheb

9.Theoretical and computational decay results for a Bresse system with
one infinite memory in the longitudinal displacement, Mohamed
Alahyane, Mohammad M. Al-Gharabli and Adel M. Al-Mahdi

10. Controllability results for Sobolev type Hilfer fractional
backward perturbed integro-differential equations in Hilbert space,
Ichrak Bouacida, Mourad Kerboua and Sami Segni

11.Cauchy problem for a fractional anisotropic parabolic equation in
anisotropic Holder spaces, Sergey Degtyarev

12.Optimal control of the 3D damped Navier-Stokes-Voigt equations with
control constraints, Sakthivel Kumarasamy

13. Controllability of retarded time-dependent neutral stochastic
integro- differential systems driven by fractional Brownian motion,
Youssef Benkabdi and El Hassan Lakhel

14.Existence and regularity in inverse source problem for fractional
reaction-subdiffusion equation perturbed by locally Lipschitz sources,
Tran Van Tuan

15. A sharp Gagliardo-Nirenberg inequality and its application to
fractional problems with inhomogeneous nonlinearity, Divyang
G. Bhimani, Hichem Hajaiej, Saikatul Haque and Tingjian Luo

16. Asymptotic analysis of an age-structured predator-prey model with
ratio-dependent Holling b functional response and delays, Dongxue Yan,
Yuan Yuan and Xianlong Fu


End of Digest