Today's Editor:
Alex Townsend
Cornell University
townsend@cornell.edu
Today's Topics:
The deal.II library version 9.8 released
New software: pure-Python 2D FEM capacitor solver
Second International Conference on Approximation Theory and Applications
Call for Abstracts: International Conference (CMMAI 2026)
PhD/Postdoc positions, Computational Physics and Biofluid Mechanics, UPC, Barcelona
PhD position: Kernel Methods for Randomised Numerical Linear Algebra
PhD position in Numerical Analysis at the University of Leeds
Two postdoctoral positions in the Mathematical and Computational Foundations of Artificial Intelligence
Postdoctoral Research Positions (Ref. 26/13) at the Weierstrass Institute in Berlin
Junior professorship (tenure track) in Numerical Mathematics, TU Braunschweig, Germany
See this issue of NA Digest on the web at:
https://na-digest.coecis.cornell.edu/na-digest-html/26/v26n34.html
Submissions, FAQs, and archives:
https://na-digest.coecis.cornell.edu/
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From: Timo Heister heister@clemson.edu
Date: August 20, 2026
Subject: The deal.II library version 9.8 released
Version 9.8.0 of deal.II, the object-oriented finite element library
awarded the J. H. Wilkinson Prize for Numerical Software and the 2025
SIAM/ACM Prize in Computational Science and Engineering, has been
released. It is available for free under an Open Source license from
the deal.II homepage at
https://www.dealii.org/
- Substantially extended support for meshes that contain triangles,
tetrahedra, wedges, and pyramids
- Improved support for and performance on GPUs
- Support for newer versions of Trilinos that build on Tpetra
- Much extended interfaces to the VTK and SUNDIALS libraries
- A lot of work on reducing memory allocations to improve performance
- Continued evolution alongside newer C++ standards
- A substantial number of new tutorial and code gallery programs
More information about changes can be found in the release preprint at
https://www.dealii.org/deal98-preprint.pdf.
The main features of deal.II are:
- Extensive documentation and 88 working example programs
- Support for dimension-independent programming
- Locally refined adaptive meshes and multigrid support
- A zoo of different finite elements
- Built-in support for shared memory and distributed parallel computing,
scaling from laptops to clusters with 300,000+ processor cores
- Interfaces to Trilinos, PETSc, SUNDIALS, UMFPACK and many other
external software packages
- Input and output for a wide variety of meshing and visualization
platforms.
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From: Ralf Becker ratwolf.zero@gmail.com
Date: August 18, 2026
Subject: New software: pure-Python 2D FEM capacitor solver
capacitor-fem is a self-contained 2-D finite-element electrostatics
solver written in pure NumPy/SciPy/Matplotlib (no mesh generators or
compiled extensions). It computes potential, electric field, stored
energy and capacitance for parallel-plate, coaxial and arbitrary CSG
geometries (rectangles, rounded rectangles, circles, Boolean
combinations).
Features:
- Structured (optionally graded) triangular mesh
- Energy-based capacitance extraction
- Optional rounded plate edges
- Machine-precision validation on the exact parallel-plate case
- Runs on desktop, Jupyter and Android (Pydroid)
Open-source under the MIT license.
Source and documentation:
https://github.com/ratwolfzero/Capacitor_FEM
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From: Stefano De Marchi stefano.demarchi@unipd.it
Date: August 16, 2026
Subject: Second International Conference on Approximation Theory and Applications
📢 II International Conference on Approximation Theory and Applications —
Gaeta, Italy | 14–18 September 2026
We are pleased to announce the II International Conference on
Approximation Theory and Applications, organized within the activities of the
U.M.I. Working Group “Teoria dell’Approssimazione e Applicazioni” (UMI–
TAA).
📍 Hotel Serapo, Gaeta, Italy
📅 14–18 September 2026
Plenary lectures:
Ana-Maria Acu — University of Sibiu
*Approximation, shape preservation and image reconstruction by neural
network operators*
Wolfgang Dahmen*— University of South Carolina
*Operator Learning and Inverse Problems*
Gitta Kutyniok — LMU Munich
*Expressivity, Stability, and Sustainability of Spiking Neural Networks*
Demetrio Labate — University of Houston
*Manifold learning via Fréchet maps* ([umi-taa.sites.dmi.unipg.it][2])
The program also features contributed talks, a poster session, lectures by the
UMI–TAA Prize winners, and a Best Poster Prize.
Registration is still open until 12 September 2026.
👉 [Conference website and registration](https://umi-
taa.sites.dmi.unipg.it/gaeta/)
We warmly invite colleagues, young researchers, PhD students, and everyone
interested in approximation theory, numerical analysis, machine learning, and
related applications to join us in Gaeta this September.
Please share this announcement with colleagues and interested research
groups.
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From: Lakshmi C cmmai2026@bharatamatacollege.in
Date: August 16, 2026
Subject: Call for Abstracts: International Conference (CMMAI 2026)
The Postgraduate and Research Department of Mathematics, Bharata Mata
College, Thrikkakara, Ernakulam, Kerala, India is pleased to invite researchers,
faculty members, and industry experts to submit original, previously unpublished
research abstracts for the International Conference on Computational
Mathematics, Modeling and Artificial Intelligence (CMMAI 2026).
📅 Abstract Submission Deadline: 25 August 2026 (Extended)
📢Notification of Acceptance: 27 August 2026
📝 Registration Deadline: 31 August 2026
📚 Publication Opportunity: Selected papers may be considered for publication
in the Springer Proceedings in Mathematics and Statistics (PROMS) series,
subject to peer review and publisher approval
🔗 Submit your Abstract: https://forms.gle/q2txqyNyemcRWooj8
🔗 Register for the Conference: https://forms.gle/befCZLcaTzYgymEC8
📍 Venue: Bharata Mata College (Autonomous), Thrikkakara
🌐 Conference Website: cmmai2026.bharatamatacollege.in
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From: Eric Neiva eric.neiva@upc.edu
Date: August 17, 2026
Subject: PhD/Postdoc positions, Computational Physics and Biofluid Mechanics, UPC, Barcelona
The newly-formed research group in Computational Physics and
Biofluid
Mechanics (CoPhyBiM) at the Universitat Politècnica de Catalunya
(Barcelona)
invites applications for PhD and postdoctoral positions in
multiscale modelling
of atherosclerosis progression driven by environmental factors.
The PhD or postdoctoral researcher will join the ADHERE project,
funded by
the Spanish State Research Agency (AEI). ADHERE develops next-
generation
computational methods to investigate how environmental factors
influence
the progression of atherosclerosis, combining mathematical
modelling with
experimental and clinical research.
For further information and application instructions, please visit:
https://ericneiva.com/call-for-eois-for-adhere-project.html
Please send your questions to biofluids@mylist.upc.edu
Applications received by 30 September 2026 will receive full
consideration.
-------------------------------------------------------
From: Nick Polydorides npolydor@ed.ac.uk
Date: August 18, 2026
Subject: PhD position: Kernel Methods for Randomised Numerical Linear Algebra
Randomised Numerical Linear Algebra (RNLA) underpins scalable algorithms
for large-scale matrix computations, including least-squares regression, low-
rank approximation, and subspace embedding. Central to these methods is
constructing subsampling distributions such as those based on statistical
leverage scores, that preserve matrix geometry. However, computing or
approximating these distributions efficiently and reliably at scale when exact
scores are prohibitively expensive remains a major computational bottleneck.
This project - to start Fall 2027 - will investigate novel connections between
RNLA subsampling and kernel-based distribution approximation to develop
new theoretical foundations and practical algorithms for constructing compact,
representative matrix sketches. Depending on candidate strengths and
interest, the research offers scope for both rigorous theoretical contributions
such as establishing formal guarantees relating sketch quality to downstream
algorithm performance, and computational implementation on large-scale
problems.
Sitting at the intersection of numerical linear algebra, approximation theory, and
kernel methods, this project advances the foundational algorithms powering
modern large-scale data analysis and scientific computing. It is ideal for
candidates in Applied Mathematics, Theoretical Computer Science, or
Quantitative Engineering with a solid background in linear algebra and
probability. Familiarity with randomised algorithms or functional analysis is
desirable but optional.
Interested applicants should contact npolydor@ed.ac.uk before January 2027
to discuss funding options.
-------------------------------------------------------
From: Massimiliano Fasi m.fasi@leeds.ac.uk
Date: August 20, 2026
Subject: PhD position in Numerical Analysis at the University of Leeds
The School of Computer Science at the University of Leeds
invites applications for a fully funded PhD position in
numerical analysis. The project aims to design and analyse
mixed-precision algorithms for solving linear algebra
problems on exascale architectures.
Applicants should have a background in numerical analysis,
scientific computing, or a related field. Programming
experience in a scientific computing environment is desirable.
The successful candidate will develop expertise in numerical
linear algebra and high-performance computing. The position
is fully funded and is open to international applicants.
For further details and to apply, please visit:
https://tinyurl.com/leeds-mixed-precision-nla-2026
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From: Coralia Cartis coralia.cartis@maths.ox.ac.uk
Date: August 15, 2026
Subject: Two postdoctoral positions in the Mathematical and Computational Foundations of Artificial Intelligence
We invite applications for a Postdoctoral Research Associate (PDRA) to join the
EPSRC Hub on the Mathematical and Computational Foundations of Artificial
Intelligence. Applicants are expected to have published in leading machine
learning conferences or similar venues. One or two PDRAs will be recruited to
work within one of, or across, the four research themes: Learning with
Structured & Geometric Models, Low Effective-dimensional Learning Models,
Implicit Regularization, and Reinforcement Learning through Stochastic Control.
There are two two-year, fixed-term positions, funded by a research grant from
the EPSRC and the Mathematical Institute, and one will have emphasis on
optimization aspects of the above themes. The start date for this post is
flexible. The successful candidate will be expected to conduct research which
falls within the remit of this large-scale project and will have the opportunity to
do so collaboratively with other members of the hub, both at Oxford and/or with
hub partners which include universities as well as companies and governmental
organisations.
For more details on these positions and how to apply, see:
https://www.maths.ox.ac.uk/node/82115
Closing date: 12.00 PM UK time on Monday, 14 September 2026. Please note
that reference letters must also be received by this date.
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From: Weierstrass Institute hr@wias-berlin.de
Date: August 20, 2026
Subject: Postdoctoral Research Positions (Ref. 26/13) at the Weierstrass Institute in Berlin
The Weierstrass Institute for Applied Analysis and Stochastics (WIAS) invites
applications for three Postdoctoral Research Positions (f/m/d)
(Ref. 26/13) in the Research Group “Data-Driven Mathematical Modeling”
(Head: Prof. Dr. Clemens Heitzinger) to be filled at the earliest possible date.
This position offers the opportunity for independent scientific research aimed
at advancing your own academic qualifications.
Key Areas of Focus: A successful candidate will contribute to research in
reinforcement learning and data-driven mathematical modeling regarding
theoretical foundations and/or scientifically significant applications. For further
information:
https://www.diversityinresearch.careers/job/1972030/postdoctoral-research-position-f-m-d-ref-26-13-/
Please direct scientific queries to Prof. Dr. Clemens Heitzinger
(clemens.heitzinger@wias-berlin.de).
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From: Christian Kirches c.kirches@tu-bs.de
Date: August 18, 2026
Subject: Junior professorship (tenure track) in Numerical Mathematics, TU Braunschweig, Germany
We invite applications for a junior professorship (salary level W1) in Numerical
Mathematics at Technical University of Braunschweig, Germany. The position is
tenure-track, with progression to Associate Professor (salary level W2) after six
years, subject to a successful tenure review.
For more details on the position and how to apply, please see:
https://vacancies.tu-
braunschweig.de/jobposting/50be7f00430af98e0ec03f99b981a7b4994db037
0
Closing date: August 31, 2026, 12.00 PM CEST.
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End of Digest
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