NA Digest, V. 22, # 7

NA Digest Monday, February 21, 2022 Volume 22 : Issue 7


Today's Editor:

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

Today's Topics: 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/


From: Kris ONeill mailto:oneill@siam.org
Date: February 16, 2022
Subject: New Book, Introduction to Numerical Linear Algebra


Introduction to Numerical Linear Algebra
by Christoph Borgers

This textbook on numerical methods for linear algebra problems
presents detailed explanations that beginning students can read on
their own, allowing instructors to go beyond lecturing and making it
suitable for a 'flipped' classroom. The author covers several topics
not commonly addressed in related introductory books, including
diffusion, a toy model of computed tomography, global positioning
systems, the use of eigenvalues in analyzing stability of equilibria,
and multigrid methods. A detailed derivation and careful motivation of
the QR method for eigenvalues starting from power iteration is also
included, as is a discussion of the use of the SVD for grading.

February 2022 / x + 348 pages / Softcover / 978-1-611976-91-5 / List
$79.00 / SIAM Member $55.30 / OT178

SIAM Bookstore:
https://my.siam.org/Store/Product/viewproduct/?ProductId=3D40807989


From: Kris ONeill mailto:oneill@siam.org
Date: February 16, 2022
Subject: New Book, Sparse Polynomial Approximation of High-Dimensional Functions


Sparse Polynomial Approximation of High-Dimensional Functions
by Ben Adcock, Simone Brugiapaglia, and Clayton G. Webster

For over seven decades there has been a focused research effort on
high- dimensional approximation -- that is, the development of methods
for approximating functions of many variables accurately and
efficiently from data. This book provides an in-depth treatment of
sparse polynomial approximation methods, which have emerged as useful
tools for various high-dimensional approximation tasks arising in a
range of applications in computational science and engineering. It is
the first comprehensive and unified treatment of polynomial
approximation techniques that can mitigate the curse of dimensionality
in high-dimensional approximation, including least squares and
compressed sensing. It develops main concepts in a mathematically
rigorous manner and contains many numerical examples, each accompanied
by downloadable code.

2022 / xviii + 292 pages / Softcover / 978-1-611976-87-8 / List $84.00
/ SIAM Member $58.80 / CS25

SIAM Bookstore:=20
https://my.siam.org/Store/Product/viewproduct/?ProductId=3D40794500


From: Thomas Hagstrom mailto:thagstrom@smu.edu
Date: February 17, 2022
Subject: Finite Element Rodeo, USA, Mar 2022


On March 4--5 the Department of Mathematics at SMU will host the
Finite Element Rodeo. The Finite Element Rodeo is informal, regional
(Texas, Louisiana, and surrounding states) conference devoted to the
theory and practice of the finite element method, and related areas of
numerical analysis and partial differential equations. It has been
held annually since 1995. 10-15 minute talks are given in random
order, and postdocs/graduate students are encouraged to present. To
register see the link below. Email Tom Hagstrom, mailto:thagstrom@smu.edu, if
you have any questions.

https://people.smu.edu/sxu/2022-smu-fe-rodeo/


From: Kirk M. Soodhalter mailto:ksoodha@maths.tcd.ie
Date: February 15, 2022
Subject: UPDATE: Conference Honoring Daniel Szyld, USA, Mar 2022


Barring unexpected complications, we confirm that indeed this
conference will take place - fully live and in person. The venue,
Temple University, requires that all participants be fully vaccinated.
We ask that all participants (invited speakers and other
contributors/attendees) please do register before the deadline of 24
February. Further details can be found at the conference website
https://www.maths.tcd.ie/~ksoodha/szyld2022/.

We will look forward to seeing you there,
Kirk M. Soodhalter, Christopher Beattie, Howard Elman


From: Dirk Praetorius mailto:dirk.praetorius@asc.tuwien.ac.at
Date: February 18, 2022
Subject: Finite Element Methods and Adaptivity, Austria, Mar-Apr 2022


The workshop "CC2LX - Workshop on Finite Element Methods and
Adaptivity" will be held on March 31 and April 01, 2022 at TU Wien on
the occasion of the 60th birthday of Professor Carsten Carstensen (HU
Berlin, Germany). We invite friends, academic family, and researchers
working in the field to participate in the 2-day workshop and
celebrate with him.

The workshop will consist of invited and contributed talks, which are
held in presence. Online participation (without a talk) will be
possible via Zoom.

Deadline for abstract submission: March 01, 2022
Further Information: https://www.asc.tuwien.ac.at/cc2lx/


From: Rolf Stenberg mailto:rolf.stenberg@aalto.fi
Date: February 17, 2022
Subject: European Finite Element Fair, Finland, Jun 2022


The 19th European Finite Element Fair will take place on 3-4 June 2022
at Aalto University, Helsinki metropolitan area, Finland.

The registration deadline is May 31, 2022. (There is no conference
fee.)

For further details, see
http://math.aalto.fi/conferences/efef2022/


From: Heike Fassbender mailto:h.fassbender@tu-braunschweig.de
Date: February 18, 2022
Subject: Householder Symposium XXI, Italy, Jun 2022


The Householder Symposium XXI on Numerical Linear Algebra has been
rescheduled to be held at Hotel Sierra Silvana, Selva di Fasano (Br),
Italy, 12-17 June 2022. The meeting will in person, no virtual
participation will be offered.

The Symposium is very informal, with the intermingling of young and
established researchers a priority. Attendance is by invitation
only. Each attendee will be given the opportunity to present a talk or
a poster. Some talks will be plenary lectures, while others will be
shorter presentations arranged in parallel sessions. Participants are
expected to attend the entire meeting.

Starting February 22, 2022
* all those invited to the 2020 Householder Symposium are asked to
confirm their interest in attending the June 2022 meeting and to
submit a new abstract if appropriate,
* new applications may be submitted to fill vacancies that will occur
as a result of possible cancellations due to the postponement and
the current Covid 19 situation. Applications are welcome from
researchers in numerical linear algebra, matrix theory, and related
areas such as optimization, differential equations, signal
processing, control, and data science.

Web page: https://users.ba.cnr.it/iac/irmanm21/HHXXI/index.html
Resubmission/Application deadline: March 15, 2022
Notification of acceptance for new applications: first week of April
2022



From: Mathias J. Krause mailto:mathias.krause@kit.edu
Date: February 21, 2022
Subject: Postponed: Lattice Boltzmann Methods/OpenLB, Poland, Jun 2022


The 5th Spring School on Lattice Boltzmann Methods (#LBM) with #OpenLB
Software Lab has been postponed to take place from the 6th to the 10th
of June 2022. We are optimistic and looking forward meet in person in
Krakow, Poland.

We have updated all webpages. Details regarding the payment of your
attendance fee are now available. The registration is still open for
anyone who is interested.

See https://www.openlb.net/spring-school-2022/ for more information.


From: Tibor Csendes mailto:csendestibor@gmail.com
Date: February 21, 2022
Subject: HUGO Global Optimization, Hungary/HYBRID, Sep 2022


Call for Papers to HUGO 2020 - XV. Global Optimization Workshop
University of Szeged, Szeged, Hungary, 5-8 September 2022, hybrid
setting

This workshop organized by the University of Szeged offers a
traditional forum for researchers and practitioners to discuss new
issues, challenging problems, advanced solutions and new trends in
global optimization. Since 1985, a tradition of Global Optimization
Workshops exists that senior researchers and PhD students meet in a
single-stream session environment to discuss approaches, algorithms
and challenging applications in the field of global optimization.

Confirmed plenary speakers: Immanuel Bomze, Marco Locatelli, and Ruth
Misener.

All participants wishing to present a talk at HUGO 2022 should prepare
an extended abstract of 4 pages in LaTeX style. Detailed instructions
for preparing & submitting a manuscript will be made soon via the
conference home page http://www.inf.u-szeged.hu/hugo.

- Confirmation of participation: asap (just fill in our short form if
you are thinking about to come)
- Deadline for the submission of extended abstracts: April 30, 2022
- Notification of acceptance: May 31, 2022

Contact: mailto:hugo@inf.u-szeged.hu or any of the organizers above


From: Chiara Piccolo mailto:chiara.piccolo@metoffice.gov.uk
Date: February 20, 2022
Subject: Scientist/Software Engineering Positions, Data Assimilation


Data Assimilation (DA) is used to statistically blend observations and
numerical models. It is an essential process in producing a skilful
weather forecast. The Met Office is at the forefront of DA
applications in operational Numerical Weather Prediction. Possibly
the greatest challenge for modern DA is to consider how the complex DA
algorithms could be run efficiently on future supercomputer
architectures. Work in the DA team at the Met Office is highly
collaborative and the team has links to scientists and software
engineers in national and international organizations.

We are hiring scientists and software engineers for our DA team! Find
out more about our exciting job opportunities and apply before Sunday
27 February: https://bit.ly/3o07d5S


From: Steven Fletcher mailto:steven.fletcher@colostate.edu
Date: February 18, 2022
Subject: Postdoc Position, Data Assimilation and ML, Colorado State Univ


The Cooperative Institute for Research in the Atmosphere (CIRA) at
Colorado State University (CSU), located on the CSU Foothills Campus,
approximately 5 miles northwest of CSU main campus, seeks to fill a
postdoctoral fellowship in April/May 2022 as part of a National
Science Foundation (NSF) award to train a new scientist in data
assimilation and machine learning techniques.

This fellowship is intended for persons who have recently completed
their Ph.D and may last up to 18 months contingent upon NSF funding
availability. The individual in this position will serve as a member
of the CIRA data assimilation group and will test the robustness of
machine learning techniques to identify the links between non-Gaussian
distributions and different atmospheric scale dynamics, convert the
hybrid version of WRF-GSI(JEDI) to have a non-Gaussian component, and
assess the robustness of new non-Gaussian based ensemble systems along
with advancing the development of a new version of the Maximum
Likelihood Ensemble Smoother.

Applications will be accepted until the position is filled; however,
to ensure full consideration applications should be submitted by 11:59
PM MT on Sunday, March 13, 2022. References will not be contacted
without prior notification of candidates. Find more detail about this
position and apply electronically by clicking "Apply to this Job" at
the following website: https://jobs.colostate.edu/postings/99928.

NOTE: In your cover letter, please specifically address the required
and preferred qualifications of this position. A cover letter that
fails to address the required and preferred qualifications of this
position may not be further considered after review by the search
committee. CSU is an EO/EA/AA employer and conducts background checks
on all final candidates.


From: Idoia Hernandez mailto:recruitment@bcamath.org
Date: February 21, 2022
Subject: Postdoc Position, Inverse Methods, BCAM


Basque Center for Applied Mathematics - BCAM is offering a
Postdoctoral position in the framework of IA4TES - Inteligencia
Artifical para la Transicion Energetica Sostenible (Artificial
Intelligence for Sustainable Energy Transition) project. This job
offer, in particular, is to work in Simulation of Wave Propagation
group at BCAM with D. Pardo and V. Nava, where the researcher will
work on Deep Learning, Data-Driven Computing, Partial Differential
Equations, Inverse Problems and Offshore Wind Energy.

Contract and offer: 2 years
Deadline: 28 February 2022

More info and applications at: http://www.bcamath.org/en/research/job/ic2022-02-postdoctoral-fellow-on-inverse-methods-for-structural-health-monitoring-of-offshore-wind-energy-technologies

Requirements: Applicants must have their PhD completed before the
contract starts. PhD in Mathematics and/or Civil, Mechanical,
Industrial, Offshore Engineering or similar areas.

Skills: Good interpersonal skills. A proven track record in quality
research, as evidenced by research publications in top scientific
journals and conferences. Demonstrated ability to work independently
and as part of a collaborative research team. Ability to present and
publish research outcomes in spoken (talks) and written (papers) form.
Ability to effectively communicate and present research ideas to
researchers and stakeholders with different backgrounds. Fluency in
spoken and written English.

The preferred candidate will have: Strong background in the numerical
solution of Partial Differential Equations and/or Deep Learning
techniques. Background in Inverse Problems. Experience in treatment
of long time series. Experience in simulation of long time series.
Experience in modelling Failure Modes and Effects Analysis (FMEA) for
components / subsystems / systems. Good programming skills in Python
and preferably, also Tensorflow. Interest and disposition to work in
interdisciplinary groups. The candidate would preferably be in
possess of: Experience in the sector of offshore wind energy, or
offshore oil and gas, or structures in offshore environment.


From: Idoia Hernandez mailto:recruitment@bcamath.org
Date: February 21, 2022
Subject: Postdoc Position, Modelling Offshore Wind Energy Technologies


Basque Center for Applied Mathematics - BCAM is offering a
Postdoctoral position in the framework of IA4TES - Inteligencia
Artifical para la Transicion Energetica Sostenible (Artificial
Intelligence for Sustainable Energy Transition) project. This job
offer, in particular, is to work in Simulation of Wave Propagation
group at BCAM with D. Pardo and V. Nava, where the researcher will
work on Machine Learning, Data-Driven Computing, Numerical Simulation,
Degradation Models, Transfer Learning, Offshore Wind Energy.

Contract and offer: 2 years; Deadline: 28 February 2022, More info and
applications at:
http://www.bcamath.org/en/research/job/ic2022-02-postdoctoral-fellow-on-modelling-the-remaining-useful-lifetime-for-offshore-wind-energy-technologies

Requirements: PhD in Mathematics and/or Civil, Mechanical, Industrial,
Offshore Engineering or similar areas.

Skills: Good interpersonal skills. A proven track record in quality
research, as evidenced by research publications in top scientific
journals and conferences. Demonstrated ability to work independently
and as part of a collaborative research team. Ability to present and
publish research outcomes in spoken (talks) and written (papers) form.
Ability to effectively communicate and present research ideas to
researchers and stakeholders with different backgrounds. Fluency in
spoken and written English.

The preferred candidate will have: Experience in reliability modelling
of the remaining useful life for components/subsystems/systems using
Bayesian approaches. Experience in degradation modelling. Experience
in machine learning techniques and in particular in Transfer Learning
problems. Experience in treatment of long time series. Experience in
simulation of long time series. Good programming skills in Python and
R. Interest and disposition to work in interdisciplinary groups. The
candidate would preferably be in possess of: Experience in the sector
of offshore wind energy, or offshore oil and gas, or structures in
offshore environment.


From: Christoph Lehrenfeld mailto:lehrenfeld@math.uni-goettingen.de
Date: February 16, 2022
Subject: Postdoc Position, Research Software and Data, Univ of Goettingen


Within the Collaborative Research Center (CRC) 1456 "Mathematics of
Experiment: The challenge of indirect measurements in the natural
sciences" at the Georg-August-University Gottingen we look for another
PostDoc for the infrastructure project. The infrastructure project
supports the constituent projects of the CRC to meet the highest
standards in reproducible research and collaborate on software
projects and data. More details on the CRC and the position can be
found here: https://www.uni-goettingen.de/crc1456 and
https://www.uni-goettingen.de /de/305402.html?cid=3D15981 .


From: Kent-Andre Mardal mailto:kent-and@math.uio.no
Date: February 15, 2022
Subject: Postdoc Position, Univ of Oslo


We are searching for a highly motivated candidate with a strong
background in scientific computing (mathematics/physics/machine
learning) and a passion to work on the intersection of physics,
numerics and machine learning with application to sustainability and
hydro power.

The Postdoctoral Fellow position is a part of the Computational
Hydropower project
(https://www.mn.uio.no/math/english/research/projects/comphydro/index.html)
that aims to develop a new generation of modeling and learning tools
for applications in sustainable energy applications - with particular
focus on hydro power. The project is a collaboration between Expert
Analytics, NTNU, Statkraft and UiO.

For further information please contact: Professor Kent-Andre Mardal
(mailto:kent-and@math.uio.no)


From: Christian Offen mailto:christian.offen@uni-paderborn.de
Date: February 21, 2022
Subject: Postdoc/PhD Position, Comp Mathematics and Optimization, Paderborn Univ


The Department of Mathematics at Paderborn University is looking for a
Research Assistant (f/m/d) (pay scale E13 TV-L) with 100 % of the
regular working time. Both doctoral candidates and postdocs are
welcome. The position is to be filled as soon as possible. The
employee will be part of the group "Applied Mathematics - Numerics and
Control" of Prof. Sina Ober-Blobaum. The group's research topics are
in the field of computational mathematics and optimization with a
particular focus on structure-preserving simulation methods and modern
engineering applications such as vehicle dynamics, space mission
design or robotics. Current research projects include the areas of
optimal control of differential equations, the development and
analysis of numerical geometric integrators, the combination of
mathematical methods with learning processes, and the use of
symmetries in model predictive control. The groups homepage is
available here:
https://math.uni-paderborn.de/en/ag/research-group-applied-mathematics-numerical-mathematics-and-control

The job posting with details on requirements, the area of
responsibility, and the application process can be found here:
https://math.uni-paderborn.de/fileadmin/mathematik/ag/angewandte-mathematik/Kennziffer5160_Englisch.pdf


From: Jakub Both mailto:jakub.both@uib.no
Date: February 18, 2022
Subject: PhD Position, Appl & Comp Mathematics, Univ of Bergen, Norway


The University of Bergen invites applications for a PhD research
fellowship in Applied and Computational Mathematics, beginning between
April 1 and June 1, 2022. The position is part of the Center of
Sustainable Subsurface Resources (CSSR), a recent collaboration
between NORCE (Bergen, Norway) and the University of Bergen, Norway.

The focus of the PhD research project is the development of robust,
modular coupling strategies for accurate, reliable multi-model
simulations involving models with a potentially highly different
degree of complexity and data-reliance. This involves developing an
analytical framework for coupled problems which shall aid deriving
practical guidelines for designing solvers involving operator
splitting, multi-rate schemes, iterative coupling strategies, and
preconditioning.

Deadline for application is March 10, 2022.

For details about the position and how to apply, please see
https://www.jobbnorge.no/en/available-jobs/job/220954/phd-research-fellow-in-applied-and-computational-mathematics-nfr-centre-for-sustainable-subsurface-resources-cssr


From: Heike Sill mailto:heike.sill@wias-berlin.de
Date: February 15, 2022
Subject: PhD Position, ML for Inverse Problems, WIAS, Germany


WIAS invites applications for a PhD student position (f/m/d)
(Ref. 22/03) in the Research Group "Nonlinear Optimization and Inverse
Problems" (Head: Prof. Dr. D. Homberg) starting at April 1, 2022.

The position is tied to the project "Machine Learning for Inverse
Problems with continuous normalizing flows and mean field games" PI:
PD Dr. Martin Eigel). The goal of the project is the development and
analysis of Neural Networks for invertible measure transport such as
normalizing flows. Connections to optimal transport, optimal control,
mean field games and stochastic differential equations will be
examined. Moreover, low-rank tensor formats will be used in a hybrid
method. In collaboration with the PTB, the developed methods will be
applied to inverse problems for geometry parameters the quality
control of semiconductor manufacturing.

We are looking for candidates with a solid background in applied
mathematics, theoretical chemistry, theoretical physics, or electrical
engineering. They are expected to be familiar with some of the topics
numerical analysis (for differential equations), quantification of
uncertainty, statistical learning theory, high-dimensional
approximations, stochastic analysis. Applicants are also expected to
have experience with at least one of the popular Python frameworks for
machine learning. Previous experience in continuum mechanics,
thermodynamics, homogenization theory, software engineering, or
machine learning are beneficial.

A completed scientific university degree (master's degree) in
mathematics or a closely related field is required as well as
demonstrable programming experience preferably in python and good
communication skills in English. See here for more information:
https://short.sg/j/15845948


From: Ercilia Sousa mailto:ecs@mat.uc.pt
Date: February 20, 2022
Subject: PhD Position, Mathematics, Portugal


The UC|UP Joint PhD Program in Mathematics, run by the Universities of
Coimbra and Porto, in Portugal, welcomes applications for the academic
year of 2022/2023.

All areas of Mathematics are covered in the Program, in particular:
Algebra; Analysis/Differential Equations; Discrete
Mathematics/Combinatorics; Dynamical Systems; Geometry/Topology;
Numerical Analysis/Optimization; Probability/Statistics.

The first call for applications is open from February 1 to March 10,
2022.

To formalize the expression of interest, candidates must send the
following documents to the email mailto:cmuc@mat.uc.pt
- elements of the Citizen Card/Identity Card/Passport
- updated curriculum vitae
- certificates of qualifications
- school transcript, containing the classifications obtained in all
undergraduate and master's subjects
- motivation letter
- name and email address of two professors who must write letters of
recommendation Both letters of recommendation are mandatory. The
letter writers must send them directly to mailto:cmuc@mat.uc.pt .

The research centers associated with the program, CMUC
(https://www.mat.uc.pt/~cmuc) and CMUP (https://www.cmup.pt), will
open calls for scholarships very soon.

More information at:
http://www.mat.uc.pt/phd_prog/requirements.php?edc


From: Heike Sill mailto:heike.sill@wias-berlin.de
Date: February 21, 2022
Subject: PhD Position, Probability Theory/Stochastic Analysis, WIAS, Germany


WIAS invites applications for a PhD student position (f/m/d)
(Ref. 22/05) in the Research Group "Stochastic Algorithms and
Nonparametric Statistics" (Head: Prof. Dr. Vladimir Spokoiny) starting
at April 1, 2022.

The position is tied to the MATH+ Cluster of excellence project AA4-2:
"Optimal control in energy markets using rough analysis and deep
networks". Motivated by the complex and pivotal role of energy
markets in our economy, the project aims to develop and analyze
efficient methods for modeling energy price processes and methods for
solving stochastic control and decision problems based thereon. Some
particular methods used in the project are signature based regression,
dual methods for randomized stochastic optimal control, relevant for
energy "swing" options, Bayesian reinforcement optimal control and
last not least data driven dynamics and rough volatility.

We are looking for candidates with a master's degree in mathematics
and a strong background in probability theory and stochastic
analysis. Prior knowledge is (stochastic) optimal control, rough
analysis, statistics or machine learning is beneficial.

Please direct scientific queries to PD Dr. J. Schoenmakers
(mailto:John.Schoenmakers@wias-berlin.de) or Dr. Christian Bayer
(mailto:Christan.Bayer@wias-berlin.de). The appointment is limited until
31.03.2025. The reduced work schedule is 29,25 hours per week, and the
salary is according to the German TVoeD Bund scale.

See here for more information: https://short.sg/j/16108473


From: Kent-Andre Mardal mailto:kent-and@math.uio.no
Date: February 15, 2022
Subject: PhD Position, Univ of Oslo


Position as PhD Research Fellow in Applied Mathematics / Mechanics
available at the Department of Mathematics.

We are searching for a highly motivated candidate with a strong
background in scientific computing (mathematics/physics/machine
learning) and a passion to work on the intersection of physics,
numerics and machine learning with application to sustainability and
hydropower.

The PhD research Fellow position is a part of the Computational
Hydropower project
(https://www.mn.uio.no/math/english/research/projects/comphydro/index.html)
that aims to develop a new generation of modeling and learning tools
for applications in sustainable energy applications -- with particular
focus on hydro power. The project is a collaboration between Expert
Analytics, NTNU, Statkraft and UiO.

For further information please contact: Professor Kent-Andre Mardal
(mailto:kent-and@math.uio.no)


From: Michele Ruggeri mailto:michele.ruggeri@strath.ac.uk
Date: February 19, 2022
Subject: PhD Position, Univ of Strathclyde, UK


The Department of Mathematics and Statistics of the University of
Strathclyde invites applications for a PhD studentship to work on the
project "Soft Matter with Nematic and Magnetic Order: Models,
Simulations and Applications" under the supervision of Prof. Apala
Majumdar and Dr Michele Ruggeri.

The aim of the project is to develop new mathematical models for
ferronematic materials to account for both the nematic and magnetic
order, and how they couple to each other. The focus is also on the
design and analysis of new numerical methods for ferronematic
systems. The mathematical models and numerical schemes will be applied
to study the experimentally observable states in prototype
ferronematics with a long term goal of designing and controlling
ferronematic systems for tailor-made applications.

A bachelor degree in Mathematics is required. Applicants should have
some experience with partial differential equations, advanced
calculus, mechanics, numerical methods and ideally some knowledge of
basic coding in any programming language.

The studentship covers home fees and stipend. Further funding
opportunities for strong international candidates will be explored.
Interested candidates should send their CV with a brief statement of
interest to Apala Majumdar (mailto:apala.majumdar@strath.ac.uk) and Michele
Ruggeri (mailto:michele.ruggeri@strath.ac.uk). Further information can be
found at the following link: http://shorturl.at/iqBFT


From: Laurette Lauffer mailto:laurette.lauffer@kit.edu
Date: February 14, 2022
Subject: Doctoral Positions, Wave Phoenomena, KIT


Within the Collaborative Research Center "Wave phenomena - analysis
and numerics" (CRC 1173) we are currently seeking to recruit, as soon
as possible, limited to three years, Doctoral Researchers (f/m/d - 75
%) for the project C2 "Seismic imaging by full waveform inversion".

We seek an ambitious doctoral researcher with strong interest both in
theoretical and practical aspects of full- waveform inversion. You
will have the opportunity to attend courses, conferences, workshops,
and summer schools. Engagement in teaching is encouraged.

The following qualifications are required: Excellent Master or an
equivalent degree in Geophysics. Strong theoretical background in
seismic imaging and inverse problems. We expect good writing and oral
communication skills in English along with the ability to work
independently within an international team. Programming skills and
experience with the modeling and inversion of seismic waveforms are a
plus.

Applications should include a cover letter, a curriculum vitae, a
statement of research interest, contact information for two referees,
and copies of degree certificate(s) in one pdf.

For further information see: https://www.waves.kit.edu/joboffers.php


From: Masoud Hajarian mailto:m_hajarian@sbu.ac.ir
Date: February 14, 2022
Subject: New Journal, CMCMA


With great pleasure we announce the launch of our new journal:
Computational Mathematics and Computer Modeling with Applications
(CMCMA) https://cmcma.sbu.ac.ir/.

CMCMA is an international journal published by Shahid Beheshti
University, Tehran, Iran, founded in 2022.

CMCMA is open access and free of charges.

Submissions should be sent online in the web site:=20
https://cmcma.sbu.ac.ir/.

Refereeing process: Our review process type is the single-blind peer
review.

CMCMA publishes high-quality original research papers in all areas of
modelling, applied and computational mathematics. Appropriate areas
include, but are not limited to: Tensor computations and applications;
Numerical linear algebra; Application of methods of numerical linear
algebra in science, engineering and economics; Machine learning;
Numerical optimization; Computational statistics; Control systems;
Iterative methods for nonlinear equations; Fast numerical algorithms;
Parallel computations; Numerical solutions of PDEs; Theory and
computations of non-local modelling and fractional partial
differential equations; Imaging algorithms, deep neural network
configurations and vision restorations; Stochastic partial
differential equations; Computational finance and applications;
Computational medicine, biomedicine and epidemiology; Inverse problems
and data analysis; Modeling using PDEs; Analysis of mathematical
models, formulated in terms of PDEs; Discretization methods and
numerical analysis for PDEs; Verification and validation;
Interpolation and approximation; Integral equations.


From: Saul Buitrago Boret mailto:sbutrago@usb.ve
Date: February 14, 2022
Subject: Contents, Bulletin of Computational Applied Mathematics, 9 (2)


Table of Contents
Bulletin of Computational Applied Mathematics, Vol.9, N2
http://www.compama.co.usb.ve/table-of-contents
https://sites.google.com/usb.ve/bullcompama/table-of-contents

Detection of discontinuity points in one variable functions using
spaces of trigonometric functions, Pablo Palma, Rodolfo Gallo, Raul
Manzanilla

Prediction of trending topics using ANFIS and deterministic models,
Rene Escalante, Marco Odehnal

A common fixed point theorem for compatible mappings satisfying a
contractive condition involving altering distance functions, Wilmer
Barrera

A note on the integrability of exceptional potentials via polynomial
bi-homogeneous potentials, Primitivo B. Acosta-Humanez, Martha
Alvarez-Ramirez, Teresinha J. Stuchi

Interior estimates of first order for initial value problems in the
octonion algebra, Yandry Intriago, Eusebio Ariza Garcia, Carmen Judith
Vanegas

Design of an imputation methodology by random selection using
regression trees, Lelly Useche; Jean Perez Parray; Carlos
Garcia-Mendoza; Ana Ides Chacon

One-dimensional Quaternion Fourier Transform and Some Applications,
Eusebio Ariza Garcia, Claudia Jimenez Heredia, Carlos Chipantiza

End of Digest
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