Today's Editor:
David S. Bindel
Cornell University
bindel@cornell.edu
Today's Topics:
Passing of Cleve Moler
New book, Ubiquitous Laplacian
DD30 Conference, Bogota, Dec 2026
Postdoctoral Scholarship, Geometric Deep Learning, Umeå Univ, Sweden
PhD Position in Applied and Computational Mathematics - University of Bergen, Norway
PhD Program in Mathematics (42nd Cycle) at Sapienza University of Rome, Italy
PhD position in Neural Operators for Physical Systems, University of Latvia
PhD position in numerical mathematics at Western Norway University of Applied Sciences, Norway
Contents, AIMS New Article: CAC Vol. 8, Art. 5
Contents, AIMS New Article: CAC Vol. 9, Art. 2, 4, 6
Contents, AIMS New Article: MFC Vol. 13, Art. 3-4
See this issue of NA Digest on the web at:
https://na-digest.coecis.cornell.edu/na-digest-html/26/v26n21.html
Submissions, FAQs, and archives:
https://na-digest.coecis.cornell.edu/
-------------------------------------------------------
From: David Bindel bindel@cornell.edu
Date: May 22, 2026
Subject: Passing of Cleve Moler
We are sad to share that Cleve Moler passed away on May 20, 2026, at the age
of 86, at his home and surrounded by his family:
https://www.mathworks.com/company/aboutus/founders/clevemoler.html
Cleve was an important member of the community (and a long-time editor of
NA Digest). We anticipate a longer post in his memory in an upcoming NA
Digest.
-------------------------------------------------------
From: Xiangxiong Zhang zhan1966@purdue.edu
Date: May 18, 2026
Subject: New book, Ubiquitous Laplacian
Ubiquitous Laplacian: An Introduction to Numerical PDEs with
Applications in Data Science, by Rongjie Lai and Xiangxiong Zhang
This graduate-level textbook introduces numerical methods for PDEs
through the unifying perspective of the Laplacian, with connections
to scientific computing and modern data science.
The first part covers classical numerical methods for the Laplacian
and Poisson equation, including finite difference and finite element
methods, together with applications to various PDE models. The
second part focuses on the Laplace-Beltrami operator on triangular
meshes and discrete Laplacians for point cloud representations of
manifolds.
The book includes homework problems and research-oriented projects
suitable for graduate instruction and self-study.
World Scientific, 2026
DOI: https://doi.org/10.1142/14349
Freely available sample content:
https://www.math.purdue.edu/~zhan1966/book/Laplacian/index.html
-------------------------------------------------------
From: Juan Galvis on behalf of the LOC of DD30 dd30colombia@unal.edu.co
Date: May 20, 2026
Subject: DD30 Conference, Bogota, Dec 2026
The 30th International Conference on Domain Decomposition Methods
dd30 will take place in Bogota, Colombia, Dec 6-11, 2026,
at Universidad Nacional de Colombia.
DD30 will bring together researchers in DD, NA, scientific computing,
HPC, multiscale methods, parallel computing, and AI forscientific
modeling.
This will be the first DD conference held in Latin America.
Speakers: Alfio Quarteroni (2026 Olof B. Widlund Prize), Marsha
Berger, Juan Calvo, Victorita Dolean, Yalchin Efendiev, Luca Pavarino,
Rongliang Chen, Li Luo, Tommaso Vanzan, Marcella Bonazzoli, Wei Gong,
and ShuLin Wu.
Submission of ms proposals and abstracts for talks and posters is
now open.
https://ingenieria.bogota.unal.edu.co/DD30/
https://www.ddm.org/
-------------------------------------------------------
From: Fredrik Ohlsson fredrik.ohlsson@umu.se
Date: May 19, 2026
Subject: Postdoctoral Scholarship, Geometric Deep Learning, Umeå Univ, Sweden
The Department of Mathematics and Mathematical Statistics at Umeå
University invites applications for a two-year postdoctoral
scholarship in geometric deep learning.
Project: Geometry-Aware Autoencoders for Reliable Anomaly Detection.
The project develops neural ODE / flow-based autoencoder methods on
stratified spaces for anomaly detection under geometric and
topological constraints, with applications to simulated particle
detector data, e.g., LHC data.
Relevant backgrounds include mathematics, physics, computer science,
scientific machine learning, differential geometry, differential
equations, geometric deep learning, and ML for particle physics. Good
programming skills and documented experience implementing ML models
are required.
Location: Umeå, Sweden.
Start: 1 September 2026 or by agreement.
Stipend: 750,000 SEK over two years, tax-free.
Deadline: 31 May 2026.
Full details and application:
https://www.umu.se/en/work-with-us/postdoctoral-scholarships/postdoctoral-scholarship-2-years-within-geometric-deep-learning_935515/
Contact: Fredrik Ohlsson, fredrik.ohlsson@umu.se
-------------------------------------------------------
From: Ivar Stefansson ivar.stefansson@uib.no
Date: May 15, 2026
Subject: PhD Position in Applied and Computational Mathematics - University of Bergen, Norway
The position is part of the Differentiable Fracture Simulation, funded
by the Research Council of Norway. We will develop novel models and
numerical methods for fracture propagation using techniques of
differentiable simulation.
We seek a candidate with a master's degree in applied and
computational mathematics, scientific computing, computational physics
or computational geoscience. Key skills are experience with numerical
methods for PDEs, mathematical modelling and collaborative/open-source
software development.
Application deadline: June 4th, 2026
Read more and apply: https://www.jobbnorge.no/en/available-jobs/job/302007/phd-research-fellow-in-applied-and-computational-mathematics
-------------------------------------------------------
From: Davide Torlo davide.torlo@uniroma1.it
Date: May 22, 2026
Subject: PhD Program in Mathematics (42nd Cycle) at Sapienza University of Rome, Italy
The call for the PhD Program in Mathematics (42nd Cycle) at Sapienza
University of Rome is now officially open.
We welcome applications from motivated candidates with backgrounds in
Mathematics, Numerical Analysis, and Scientific Computing. Notably, an
increased scholarship is available for the first-ranked winning
candidate holding a foreign degree and resident abroad.
* Deadline: June 17, 2026, at 14:00 CET.
* Duration: 3 years (starting Autumn 2026).
* Selection: Based on CV, motivation/recommendation letters, and an oral
interview (available remotely).
Key Links:
* Official PhD Call & Application Portal
https://phd.uniroma1.it/web/concorso42.aspx?s=&i=3519&m=&l=EN
* Numerical Analysis & Scientific Computing Research Group at Mathematics
Department in Sapienza
https://sites.google.com/uniroma1.it/an-sc-research-group
Feel free to contact the member of the research group for more information.
Please share this opportunity with your master’s students and graduates.
-------------------------------------------------------
From: Leandro Farina farina@alum.mit.edu
Date: May 15, 2026
Subject: PhD position in Neural Operators for Physical Systems, University of Latvia
The University of Latvia is ofering a funded PhD position in the area
of physics-informed neural operators for modelling complex physical
processes governed by partial diferential equations.
The PhD project combines applied mathematics, deep learning, and
scientifc computing, with a strong emphasis on operator learning
methods such as DeepONet and Fourier Neural Operators, including their
physics-informed extensions. The research will focus on developing
theoretical understanding and practical improvements of neural
operators, with direct relevance to challenging applications in
hydrodynamics, in particular crystal growth processes and wave
dynamics in coastal and harbour environments.
The work is theory-driven but closely connected to applications: the
goal is to develop mathematical and algorithmic insights that improve
robustness, generalization, and physical consistency of neural
operators used as fast surrogate models for PDE-based simulations.
We are particularly interested in candidates with a background in
applied mathematics, especially those working at the interface of
mathematical modelling or theoretical physics, with a solid
understanding of PDEs and numerical methods, and some prior experience
in deep learning (e.g. training neural networks, familiarity with
modern ML frameworks).
The PhD position is funded for up to three years. The project-funded
salary is approximately 2000 EUR per month before tax and corresponds
to the funded workload within this project rather than a full-time
appointment. Depending on the candidate’s profile and interests,
there may also be opportunities for additional paid involvement in
related machine learning and AI-for-science projects at the University
of Latvia, as well as participation in international research
collaborations.
If you are interested, or if you know suitable candidates, please feel
free to contact the project coordinator Jānis Virbulis directly, or
Leandro Farina for an informal initial discussion.
Jānis Virbulis
e-mail: janis.virbulis@lu.lv
Leandro Farina
e-mail: farina@alum.mit.edu
-------------------------------------------------------
From: Carina Bringedal carina.bringedal@hvl.no
Date: May 17, 2026
Subject: PhD position in numerical mathematics at Western Norway University of Applied Sciences, Norway
At Western Norway University of Applied Sciences, Norway, we have a
PhD position open in numerical mathematics.
The position is part of the RCN-funded project «Physics-Adapted
Numerical Methods for Two-Phase Flow» (PANum). The position is for a
fixed-term period of 3 years with a possibility of a 4th year with
career-promoting work, such as teaching duties.
We are looking for motivated candidates with a master's degree in
computer science, simulation science, applied mathematics, or similar,
with experience in numerical analysis for ODEs/PDEs and scientific
programming.
The application deadline is June 5th 2026.
Read more and apply:
https://www.jobbnorge.no/en/available-jobs/job/300280/phd-research-fellow-in-numerical-mathematics
If you have any questions about the position, do not hesitate to
contact me
carina.bringedal@hvl.no
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: May 15, 2026
Subject: Contents, AIMS New Article: CAC Vol. 8, Art. 5
Communications on Analysis and Computation
Volume: 8, Art. 5
June 2026
https://www.aimsciences.org/CAC/article/2026/8/0
Spatial regularity of mild solutions for SPDEs with piecewise constant coefficients
Huihui Cheng
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: May 21, 2026
Subject: Contents, AIMS New Article: CAC Vol. 9, Art. 2, 4, 6
Communications on Analysis and Computation
Volume: 9, Art. 2, 4, 6
September 2026
https://www.aimsciences.org/CAC/article/2026/9/0
Factorization method for the biharmonic scattering problem for an absorbing
penetrable scatterer
Rafael Ceja–Ayala, Isaac Harris and General Ozochiawaeze
A novel analysis of an alternating algorithm for solving the Cauchy problem for a
fractional-order partial differential equation
Abdallah Bradji and Daniel Lesnic
A two-level Nyström–Schur preconditioner for indefinite least squares problem
Peizhe Li and Kailiang Xin
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: May 21, 2026
Subject: Contents, AIMS New Article: MFC Vol. 13, Art. 3-4
Mathematical Foundations of Computing
Volume: 13, Art. 3-4
October 2026
https://www.aimsciences.org/mfc/article/2026/13/0
An explicit characterization for the proximal operator of the capped lq-norm
Rongrong Lin, Haitao Yu and Yulan Liu
Optimal control via neural networks: Determination of source term in fractional
diffusion equations using alternating direction multiplier method
Abdessamad Oulmelk, Mohammed Srati, Lekbir Afraites, Aissam Hadri, Mahmoud
A. Zaky and Ahmed S. Hendy
-------------------------------------------------------
End of Digest
**************************