Subject: NA Digest, V. 23, # 10

NA Digest Sunday, March 26, 2023 Volume 23 : Issue 10

Today's Editor:

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

Today's Topics:

Dr. Ronald H.W. Hoppe (1951 - 2023)
Editor for arXiv category cs.CE
SIAM UKIE Annual Meeting, UK, Apr 2023
IPCO 2023, USA, Jun 2023
Coupled Complex Systems Modelling & Appl, Canada, Aug 2023
Computer Aspects of Numerical Algorithms, Poland, Sep 2023
Tenure-Track Position, Scientific ML, CWI Amsterdam
Research Technician Position, Statistical Machine Learning, BCAM
Postdoc Position, Computational Mathematics, INESC-ID, Portugal
Postdoc Position, Institut Polytechnique de Paris, France
Postdoc Position, Modelling and Optimization, Univ College London
Postdoc Position, Statistical Machine Learning, BCAM
PhD Position, Numerical Modelling, Heriot-Watt Univ, Scotland
PhD Positions, Univ of Munster
Contents, J Machine Learning for Modeling and Computing, 3 (4)
Contents, Mathematical Modelling and Analysis, 28 (2)

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From: Jiwen He [log in to unmask]
Date: March 23, 2023
Subject: Dr. Ronald H.W. Hoppe (1951 - 2023)

We are deeply saddened to inform you of the passing of Dr. Ronald H.W.
Hoppe on February 8, 2023, in Bad Bentheim, Germany. Dr. Hoppe was a
highly respected and cherished member of our community, and his loss
is felt profoundly by all who knew him.

Dr. Hoppe's professional journey was remarkable and inspiring, and his
contributions to the development and growth of applied and
computational mathematics were significant on a global scale. He was
born on April 10, 1951, in Nordhorn, Germany, and earned his diploma
in mathematics with a secondary subject in physics from the Technische
Universitat Berlin in 1975. Dr. Hoppe completed his doctoral thesis in
1979 and obtained his habilitation in 1986.

Throughout his academic career, Dr. Hoppe held various academic
positions at institutions across the globe, including the University
of Linkoping in Sweden and the Courant Institute of Mathematical
Sciences in New York, USA. He was appointed to the C3-Professorship at
the Mathematical Institute of TU Munich in 1990 and later the C4-
Professorship at the Faculty of Mathematics and Natural Sciences at
the University of Augsburg.

Dr. Hoppe was known for his significant contributions to the field of
numerical partial differential equations and optimization, with a
focus on multigrid methods, adaptive finite element methods, and
optimal control problems. His work had real-life applications, such as
microfluidic biochips and electrorheological fluids. He authored
several books and over 200 scientific articles during his career and
advised over 20 Ph.D. students and numerous postdoctoral
fellows. Dr. Hoppe also served on several editorial boards and had an
impressive international network of friends and colleagues due to his
natural scientific ability, patience, willingness to listen,
affability, and love for conversation.

Dr. Hoppe joined the Department of Mathematics at the University of
Houston in 2002 as a professor and continued to make significant
contributions to his field until his passing. He will be remembered as
a brilliant mathematician, an exceptional teacher, a supportive
colleague, and a dear friend.

During this difficult time, our thoughts and deepest condolences go
out to Dr. Hoppe's family, friends, and colleagues.

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From: Paolo Bientinesi [log in to unmask]
Date: March 23, 2023
Subject: Editor for arXiv category cs.CE

The Computer Science section of arXiv (arxiv.org), also known as CoRR
(Computing Research Repository), is an open source repository for
preprints in the field of computing. Preprints are organized into
subject areas, known as Categories. At submission, authors select one
or more categories, and for each category a volunteer editor checks
whether or not the submission is appropriate for the topics included
in the category. Editors do not review the submissions for quality,
only for appropriateness; such reviews typically can be done in a
couple of minutes or so each. I am currently the gatekeeper for the
category cs.CE: Computational Science, Engineering and Finance. CoRR
is looking for a volunteer willing to work with me, and eventually
succeed me, as Editor for this category. The position provides one
with a unique perspective on current research being undertaken in
these areas. About 2-4 such papers are submitted each day, so the
workload is modest. If you are interested in performing this service
to the community please contact me.



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From: Hussam Al Daas [log in to unmask]
Date: March 24, 2023
Subject: SIAM UKIE Annual Meeting, UK, Apr 2023

The SIAM UKIE Annual Meeting 2023 will be held at Trinity College
Dublin, Ireland on the 21st of April 2023. The meeting will be held
in person and virtually. We encourage participants especially students
(see next paragraph) to attend in person. Registration is free but
required. So please register at
https://www.maths.tcd.ie/~ksoodha/siamukie2023/ by Friday 31st of
March.

Travel support is available for student members of SIAM UKIE. To
apply, send your CV to Hussam Al Daas [log in to unmask]

The meeting features four invited speakers, graduate students
ten-minute talks, and the business meeting of the UKIE section. We
hope that students presenting ten-minute talks attend in person.

The list of invited speakers is:
- Reidun Twarock (University of York)
- Julian Hall (University of Edinburgh)
- Miguel Bustamante (University College Dublin)
- Sergiy Zhuk (IBM Dublin)

If you have any questions, please send them to Hussam Al Daas.

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From: Alberto Del Pia [log in to unmask]
Date: March 21, 2023
Subject: IPCO 2023, USA, Jun 2023

The 24th Conference on Integer Programming and Combinatorial
Optimization (IPCO XXIV) will take place on June 2123, 2023 at the
University of Wisconsin-Madison, Madison (WI), USA. The IPCO
conference will feature a poster session and a best poster award. The
poster session will take place on June 21, 2023.

We particularly welcome posters from Ph.D. students and
postdocs. Poster abstracts can be submitted at
https://forms.gle/vKkv4sq5PaSh1MtZ8. The abstract format is: a PDF
file, one letter-size page maximum, one-inch margins, 11-point font,
single-space. The deadline for poster abstract submissions is April 1,
2023.

The local committee will select poster presenters, subject to the
number of available poster slots. A committee will evaluate posters
during the poster session and select the best poster. Travel support
for a limited number of students will be provided by the Air Force
Office of Scientific Research (AFOSR) and the Office of Naval Research
(ONR).

The committee will communicate notifications of acceptance by April
15, 2023. Poster presenters are required to register for the
conference.

Please contact [log in to unmask] if you have any questions.


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From: Sundeep Singh [log in to unmask]
Date: March 23, 2023
Subject: Coupled Complex Systems Modelling & Appl, Canada, Aug 2023

We invite you to contribute to this international multidisciplinary
event covering diverse areas of science and engineering unified by the
crucial role of coupled phenomena, physical fields, and effects, as
well as by multiple-scale interactions at the local and/or entire
system levels. The models featured here will include a comprehensive
range of areas from the recent progress in better understanding many
physical, engineering, biological, and social systems. The symposium
welcomes theoretical, computational, and experimental advances in this
pivotal field. Further details are at
http://ammcs.wlu.ca/2023/special-sessions/ccsms/

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From: Przemyslaw Stpiczynski [log in to unmask]
Date: March 22, 2023
Subject: Computer Aspects of Numerical Algorithms, Poland, Sep 2023

16th Workshop on Computer Aspects of Numerical Algorithms (CANA'23)
Poland, Warsaw, 17 - 20 September, 2023
(https://fedcsis.org/sessions/css/cana)
in conjunction with Federated Conference of Computer Science and
Information Systems https://fedcsis.org/

Numerical algorithms are widely used by scientists engaged in various
areas. There is a special need of highly efficient and easy-to-use
scalable tools for solving large scale problems. The workshop is
devoted to numerical algorithms with the particular attention to the
latest scientific trends in this area and to problems related to
implementation of libraries of efficient numerical algorithms.

Topics (including but not limited to): Parallel numerical algorithms;
Novel data formats for dense and sparse matrices; Libraries for
numerical computations; Numerical algorithms testing and benchmarking;
Analysis of rounding errors of numerical algorithms; Languages, tools
and environments for programming numerical algorithms; Numerical
algorithms on GPUs; Paradigms of programming numerical algorithms;
Contemporary computer architectures; Heterogeneous numerical
algorithms; Applications of numerical algorithms in science and
technology.

Contact: [log in to unmask]

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From: Benjamin Sanderse [log in to unmask]
Date: March 24, 2023
Subject: Tenure-Track Position, Scientific ML, CWI Amsterdam

The Scientific Computing group at CWI has a vacancy for a tenure track
position in Scientific Machine Learning and Uncertainty
Quantification.

This is a really exciting research position, where you have several
years and lots of freedom to develop your own research line within our
group. CWI in Amsterdam is a fantastic place to work, breathing an
atmosphere of scientific creativity and top-notch research, with close
connection to applications, and right in the heart of the Amsterdam
Science Park.

The full vacancy description is available online at
https://www.cwi.nl/en/jobs/vacancies/989225/ .

The vacancy fits within our broader efforts in Scientific Machine
Learning, which includes the organisation of a Semester Programme in
fall this year. The Semester Programme website is already online at
https://www.cwi.nl/en/events/cwi-research-semester-programs/research-
programmes-in-2023/research-semester-programme-on-scientific-
machine-learning/, with a more official announcement following in the
coming weeks.

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From: Idoia Hernandez [log in to unmask]
Date: March 22, 2023
Subject: Research Technician Position, Statistical Machine Learning, BCAM

The project's goal is to research and develop novel statistical
machine learning and inference methods for predictive and prescriptive
tasks that overcome the challenges posed by applied settings (e.g.,
non-stationary and missing not-at-random phenomena), combining
probabilistic models, deep learning, stochastic processes and
approximate inference. The candidate will work under the supervision
of Ikerbasque Research Fellow Inigo Urteaga, and will benefit from
close collaboration with members of the Machine Learning group at BCAM
and external collaborators at Columbia University. The core of the
research is on the design and implementation of novel machine learning
solutions within the following research challenges: 1. How to
disentangle data missingness patterns from time-varying signals of
interest via statistical machine learning models. 2. How to devise
data-driven, automated sequential decision making algorithms in
dynamic and multi-scale prescriptive environments. The candidate will
investigate both the theoretical and practical aspects of statistical
machine learning, with potential assessment of how the devised methods
perform in healthcare applications.

Contract: 1 year
Deadline: 14 April 2023
Applications at:
http://www.bcamath.org/en/research/job/ic2023-03-research-technician-in-statistical-machine-learning

Requirements: Master's degree in Computer Science, Statistics (or a
related field), or be close to its completion. Applicants must have
an excellent academic record.

Skills: Background and experience in machine learning and statistics.
A track record in quality research, as evidenced by publications in
scientific journals and conferences of the field. Self-motivated,
independent researcher with scientific curiosity and honesty.
Demonstrated ability to work independently and as part of a
collaborative research team. Good interpersonal skills, with ability
to present and publish research outcomes in spoken and written form.
Fluency in spoken and written English.

The preferred candidate will have: Familiarity with statistical
modeling, machine learning and approximate inference. Expertise with
generative modeling, stochastic processes and approximate inference.
Familiarity with reinforcement learning concepts, if interested in
working on the design of sequential decision algorithms. Solid
programming skills in Python, experience with PyTorch/JAX would be
ideal.

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From: Juan A. Acebron [log in to unmask]
Date: March 22, 2023
Subject: Postdoc Position, Computational Mathematics, INESC-ID, Portugal

The research center INESC-ID in Lisbon invites interested candidates
to apply for a postdoctoral position focusing on the development of
new Monte Carlo algorithms for computing efficiently matrix functions
for current and future high performance supercomputers. This position
is funded by the Portuguese Science Foundation FCT, and the successful
candidate will be part of an integrated team led by Prof. Jose
Monteiro and Prof. Juan A. Acebron. Candidates should have a Ph.D. in
Applied Mathematics, Physics, Computer Science or a related
field. They should possess a solid knowledge in applied mathematics,
numerical methods, good programming skills, and a proven publication
record.

Successful candidates will be able to work well within small cross
disciplinary teams, including working with researchers using both
theoretical and computational mathematics. Experience with common
scientific computing methods, computational tools, mathematical
software, and parallel computing is highly desired.

The successful Post Doctoral Fellow will interact closely with
national and international collaborators and will have the opportunity
to publish in high impact journals, present their work at
international conferences and gain access to major supercomputing
facilities through existing networks of collaborative partners.

This is a one-year appointment, eventually renewable up until 3
years. There are no teaching duties associated with this position.

How to apply: Qualified candidates should follow the instructions
described in https://euraxess.ec.europa.eu/jobs/85721

The deadline is on April 7 2023

For further information of the project see the website
http://ura.inesc-id.pt

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From: Mahdi Moeini [log in to unmask]
Date: March 21, 2023
Subject: Postdoc Position, Institut Polytechnique de Paris, France

We are looking for an outstanding young researcher with a PhD in
Mathematical Optimization or a related field, and interests in
Artificial Intelligence and Data Science.

With a focus on confluence of Data Science and Artificial
Intelligence, the post-doc is expected to do research on modern
optimization algorithms for solving the subset selection problem and
its variants.

The research will be supervised by professors "Walid Ben Ameur" and
"Mahdi Moeini" at the Institut Polytechnique de Paris (Telecom
SudParis/SAMOVAR). To be eligible, applicants must have defended - or
be due to defend - their PhD between 1 September 2020 and 31 August
2023. The postdoctoral fellowship will be provided for a 12-month
period, and can be renewed for another 12 months. Fluency in English
is a must, and having good programming skills is required.
Familiarity with Julia and a standard optimization solver, e.g.,
Gurobi or IBM Cplex, is considered as a bonus point.

The application deadline for the position is April 9th, 2023.
Applicants should apply by sending (as a single pdf file): a cover
letter, a CV (including the list of publications), and at least two
recommendation letters to: [log in to unmask] and
[log in to unmask] .


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From: Eric Fraga [log in to unmask]
Date: March 26, 2023
Subject: Postdoc Position, Modelling and Optimization, Univ College London

Applications are invited for a research associate position in the
Department of Chemical Engineering at UCL. The project aims to advance
fundamental understanding of the unusual thermodynamic and kinetic
phenomena underpinning the dissolution, aggregation, and denaturation
processes of particles generated during nuclear fuel debris retrieval
under various environments. A multidisciplinary approach will be
followed whereby experimental studies will be combined with
simulations and modelling under uncertainty to predict the debris
particle behaviour. The post is funded by an EPSRC UK-Japan Civil
Nuclear Research grant and it is in collaboration with Prof Giota
Angeli in the Department and with Prof Takehiko Tsukahara of the Tokyo
Institute of Technology and Waseda in Japan. The successful candidate
will be spending some time in the collaborator's lab.

The main role of the post holder will be the development of
mathematical models for the thermodynamic and kinetic phenomena,
including both detailed CFD models and surrogate models. The post
holder will also direct some of the experiments using model based
experiment design techniques to ensure the uncertainty estimates are
suitable for use in prediction. This person will also design and
implement a simulation software system based on surrogate models with
uncertainty quantification. The post holder will be required to
interact closely with the experimental researcher and with the
collaborators at the Tokyo Institute of Technology who will be
studying particle aggregation and particle characterization.

http://www.jobs.ac.uk/job/CYG494/research-fellow-in-modelling-and-optimization-for-elucidation-of-nano-effects

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From: Idoia Hernandez [log in to unmask]
Date: March 22, 2023
Subject: Postdoc Position, Statistical Machine Learning, BCAM

The project's goal is to research and develop novel statistical
machine learning and inference methods for predictive and prescriptive
tasks that overcome the challenges posed by applied settings (e.g.,
non-stationary and missing not-at-random phenomena), combining
probabilistic models, deep learning, stochastic processes and
approximate inference. The postdoctoral candidate will have the
opportunity to pursue their own ideas, and to lead the design and
implementation of novel machine learning solutions within the
following research challenges: 1. How to disentangle data missingness
patterns from time-varying signals of interest via statistical machine
learning models. 2. How to devise data-driven, automated sequential
decision making algorithms in dynamic and multi-scale prescriptive
environments. The candidate will investigate both the theoretical and
practical aspects of statistical machine learning, with potential
assessment of how the devised methods perform in healthcare
applications and online digital services. The candidate will work
under the supervision of Ikerbasque Research Fellow Inigo Urteaga, and
will benefit from close collaboration with members of the Machine
Learning group at BCAM and external collaborators at Columbia
University.

Contract: 1 +1 year
Deadline: 14 April 2023
Applications at:
http://www.bcamath.org/en/research/job/ic2023-03-postdoctoral-fellow-in-statistical-machine-learning

Requirements: PhD in Computer Science, Statistics (or related field).
Applicants must have completed their PhD before the contract starts.

Skills: Background and experience in machine learning and statistics.
A track record in quality research, as evidenced by publications in
scientific journals and conferences of the field. Self-motivated,
independent researcher with scientific curiosity and honesty.
Demonstrated ability to work independently and as part of a
collaborative research team. Good interpersonal skills, with ability
to present and publish research outcomes in spoken and written form.
Fluency in spoken and written English.

The preferred candidate will have: Strong background in statistical
modeling and machine learning. Expertise with generative modeling,
stochastic processes and approximate inference. Familiarity with
reinforcement learning concepts, if interested in working on the
design of sequential decision algorithms. Solid programming skills in
Python, experience with PyTorch/JAX would be ideal.

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From: Omar Laghrouche [log in to unmask]
Date: March 21, 2023
Subject: PhD Position, Numerical Modelling, Heriot-Watt Univ, Scotland

We aim to analyse data from wind turbine vibrations and investigate
the seismic wave propagation using numerical modelling. A natural
component of this study is the understanding of how best to represent
the wind turbine as a seismic source, both onshore and offshore. To
aid these investigations, we will also consider the tower and blade
response to wind, based on previous finite element modelling. The
study will include the coupling to realistic ground models, response
to wind speed and direction, and will tie the results back to a
database of observations collected from seismic sensors monitoring a
real wind farm in the UK. This project will contribute to a better
understanding of wind turbines as a source of vibration, the seismic
waves that propagate, the extent to which waves decay with distance,
and hence the critical radius of influence around sensitive
installations.

Deadline for applications: 17 April 2023

For details see:
https://www.findaphd.com/search/ProjectDetails.aspx?PJID=156673

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From: Kristina Wensing [log in to unmask]
Date: March 23, 2023
Subject: PhD Positions, Univ of Munster

Be part of Mathematics Munster!

Dive into your own research project and benefit from the excellent
research environment at the University of Munster, Germany. Doctoral
positions, as well as Ada Lovelace Fellowships, at the Cluster of
Excellence Mathematics Munster are open for application.

Apply now: Doctoral Positions. Join the Mathematics Munster Graduate
School and profit from the active and demanding research environment
for talented and motivated doctoral researchers aiming to become the
next generation of leading scientists. Salary level E13 TV-L, 75% for
three years. In all research areas related to the Cluster of
Excellence Mathematics Munster. The expected starting date is no
later than October 2023. Apply until 1 May 2023

Apply now: Ada Lovelace Fellowships. With the Ada Lovelace Fellowship
Mathematics Munster supports underrepresented groups and aims to
increase gender equality in mathematics. Salary level E13 TV-L, 25%
add-on (salary raise) for up to three years Increasing gender equality
within the mathematical sciences Fellowships must supplement a
doctoral positions and applications may be combined with the
application for a 75% PhD position. Apply until 1 May 2023.

Find more information on positions, requirements and the online
application form at:
https://www.uni-muenster.de/MathematicsMuenster/careers/apply

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From: Dongbin Xiu [log in to unmask]
Date: March 21, 2023
Subject: Contents, J Machine Learning for Modeling and Computing, 3 (4)

Journal of Machine Learning for Modeling and Computing (JMLMC)
Web: www.j-mlmc.com
ISSN Print: 2689-3967
ISSN Online: 2689-3975

Volume 3, 2022, Issue 4

Table of Content

Autoencoder neural network for chemically reacting systems, by Pei
Zhang, Ramanan Sankaran

A spatiotemporal-aware weighting scheme for improving climate model
ensemble predictions, by Ming Fan, Dan Lu, Deeksha Rastogi, Eric M.
Pierce

Geothemalcloud machine learning for geothermal resource exploration,
by Maruti K. Mudunuru, Velimir V. Vesselinov, Bulbul Ahmmed

Gradient-enchanced deep neural network approxiations, by Xiaodong
Feng, Li Zeng

An application of machine learning to college admission: the summer
melt problem, by Treena Basu, Ron Buckmire, Osei Tweneboah

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From: Raimondas Ciegis [log in to unmask]
Date: March 23, 2023
Subject: Contents, Mathematical Modelling and Analysis, 28 (2)

MATHEMATICAL MODELLING AND ANALYSIS
The Baltic Journal on Mathematical Applications, Numerical Analysis
and Differential Equations
ISSN 1392-6292, ISSN 1648-3510 online, Electronical edition:
http://mma.vgtu.lt

Raimondas Ciegis (Editor) Volume 28, Issue 2, 2023 (p.180-359)

CONTENTS

Ignas Dapsys and Raimondas Ciegis, Numerical Simulation of Fractional
Power Diffusion Biosensors

Fatima Adilova, Uygun Jamilov and Andrejs Reinfelds, On Discrete-Time
Models of Network Worm Propagation Generated by Quadratic Operators

Hanna Britt Soots, Kaido L\"{a}tt and Arvet Pedas, Collocation Based
Approximations for a Class of Fractional Boundary Value Problems

Tahar Bechouat, A Collocation Method for Fredholm Integral Equations
of the First Kind via Iterative Regularization Scheme

Kamran Suhaib, Asim Ilyas and Salman A. Malik, On the Inverse Problems
for a Family of Integro-Differential Equations

Ravi P. Agarwal, Ahmad M. Alghamdi, Sadek Gala and Maria Alessandra
Ragusa, On the Regularity Criterion on One Velocity Component for the
Micropolar Fluid Equations

Atsumasa Kondo, Strong Convergence to Common Fixed Points Using
Ishikawa and Hybrid Methods for Mean-Demiclosed Mappings in Hilbert
Spaces

Arturas Stikonas and Erdogan Sen, Asymptotic Analysis of
Sturm--Liouville Problem with Dirichlet and Nonlocal Two-Point
Boundary Conditions

Miaomiao Yang, Wentao Ma and Yongbin Ge, Barycentric Rational
Interpolation Method of the Helmholtz Equation with Irregular Domain

Virginija Garbaliauskiene, Renata Macaitiene and Darius Siauciunas, On
the Functional Independence of the Riemann Zeta-Function

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End of Digest
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