Today's Editor:
Alex Townsend
Cornell University
townsend@cornell.edu
Today's Topics:
Call for Nominations: Rising Stars in Computational & Data Sciences, April 2026
Software Release, FSML – Fortran Statistics and Machine Learning
PSBLAS 3.9.0 and AMG4PSBLAS 1.2.0
New Book, Quantum Algorithms for Optimizers
Call for Applications - Simula Summer School in Computational Physiology
Invitation to talk by Prof. Oskay (Vanderbilt) – Jan. 22, 2-3PM EST
Solving PDEs with Firedrake, Oxford, Mar 2026
Hackathon: Data Assimilation in Firedrake, 8-10 April 2026, RAL UK
9 PhD positions. Chalmers and University of Gothenburg, Sweden
PhD position, Dept. of Mathematics, University of Bergen, Norway
PhD Opportunity in Mathematical Optimisation at The University of Queensland (Australia)
PhD Opportunity in Numerical Analysis or Scientific Computing, University of Leeds
PhD opportunity in Bayesian Computational Mathematics, Linköping University, Sweden
PhD and Postdoc postions in Data Assimilation at University of Potsdam
Postdoc position in Numerical Simulation for Lattice QCD at Wuppertal University
Postdoctoral positions at Gran Sasso Science Institute, Italy
Assistant Professor position at Heriot-Watt University, Edinburgh
Contents, AIMS New Articles: JMD Vol. 21, Art. 20-22
Contents, Electronic Transactions on Numerical Analysis (ETNA)
See this issue of NA Digest on the web at:
https://na-digest.coecis.cornell.edu/na-digest-html/26/v26n2.html
Submissions, FAQs, and archives:
https://na-digest.coecis.cornell.edu/
-------------------------------------------------------
From: Jim Stewart jrstewa@sandia.gov
Date: January 08, 2026
Subject: Call for Nominations: Rising Stars in Computational & Data Sciences, April 2026
We are seeking nominations for the 2026 Rising Stars in Computational & Data
Sciences Workshop to be held April 7-8, 2026, at the Santa Fe Institute in
Santa Fe, NM. Rising Stars is an intensive workshop for graduate students and
postdocs who are interested in pursuing academic and research careers.
Nominees must be in their final year of PhD or within three years of having
graduated and not yet in a tenure-track faculty or permanent staff position.
Approximately 30 participants will be selected to come for two days of research
presentations and interactive discussions about academic and research
careers, with financial support for travel provided. Nominees are considered
based on their technical merit, and their technical and service leadership.
Nominations require (1) a letter of nomination and (2) the nominee's two-page
resume.
Nominations are due January 30, 2026 and should be submitted at:
https://app.smartsheet.com/b/form/019b37488a617a64a42d102a41da308e.
For questions, please see our FAQS linked on our website
(https://risingstars.oden.utexas.edu) or contact the Rising Stars Administrator
at rs_admin@oden.utexas.edu.
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From: Sebastian Gerhard Mutz sebastian@mutz.science
Date: January 07, 2026
Subject: Software Release, FSML – Fortran Statistics and Machine Learning
I'm pleased to announce the first (alpha) release of FSML v0.1.0 –
a modern Fortran Statistics and Machine Learning library suitable
for research, teaching, and parallel applications.
Summary
FSML includes procedures for basic statistics, statistical hypothesis
tests, statistical distributions functions, linear and non-linear
methods. Most core procedures are pure with no side effects, making
them suitable for parallel applications.
Code, Documentation, and
Resources
- The code is MIT licensed and hosted on GitHub: https://
github.com/sebastian-mutz/fsml
- Its documentation includes a
handbook and example-rich API documentation: https://
fsml.mutz.science/
- The associated paper was published in the
Journal of Open Source Software: https://doi.org/10.21105/
joss.09058
- This blog post provides more context, notes on design
choices, and where it fits into the Fortran statistics and machine
learning ecosystem: https://sebastianmutz.eu/blog/
posts/2025-12-20/
I hope some of you find the library useful and
warmly welcome any feedback, questions, suggestions, or contributions.
-------------------------------------------------------
From: Fabio Durastante fabio.durastante@unipi.it
Date: January 09, 2026
Subject: PSBLAS 3.9.0 and AMG4PSBLAS 1.2.0
We announce new versions of PSCToolkit's core components.
PSBLAS (Parallel Sparse BLAS) is a distributed sparse linear algebra library
providing scalable support for parallel sparse matrix operations, iterative
solvers, and HPC environments.
Highlights in 3.9.0:
- Direct GPU acceleration support no longer needing PSBLAS-EXT
- CMake installation support
- Improved C/C++ interface
Download: https://psctoolkit.github.io/products/psblas/
AMG4PSBLAS is an algebraic multigrid preconditioner package for PSBLAS
implementing highly parallel multilevel preconditioners.
Key
features in 1.2.0:
- Polynomial smoothers for GPU architectures
- CMake support
- Enhanced C/C++ interface
Download: https://psctoolkit.github.io/products/amg4psblas/
Both libraries include source, documentation, and examples. They support
HPC environments with MPI and optional GPU support. For support and
documentation, visit the PSCToolkit GitHub organization or project websites.
-------------------------------------------------------
From: Mitchell Graham mgraham@siam.org
Date: January 07, 2026
Subject: New Book, Quantum Algorithms for Optimizers
Quantum Algorithms for Optimizers by Giacomo Nannicini
This book presents a self-contained introduction to quantum algorithms, with a
focus on quantum optimization—quantum approaches to solving optimization
problems. It equips readers with the essential tools to assess the strengths and
limitations of these algorithms, emphasizing provable guarantees and
computational complexity.
The first comprehensive treatment of quantum optimization, Quantum
Algorithms for Optimizers provides a rigorous introduction to the computational
model of quantum computers and to the theory of quantum algorithms, contains
detailed discussions of some of the most important developments in quantum
optimization algorithms, and summarizes the most significant advances in the
open literature.
12/17/2025 / xiv + 273 pages / Softcover / 978-1-61197-875-9 / List $79.00 /
SIAM Member $55.30 / MO37
Bookstore link:
https://epubs.siam.org/doi/10.1137/1.9781611978766
-------------------------------------------------------
From: Kimberly McCabe kimberly@simula.no
Date: January 07, 2026
Subject: Call for Applications - Simula Summer School in Computational Physiology
In conjunction with the University of California, San Diego, Simula is pleased to
announce the 12th edition of our annual Summer School in Computational
Physiology. This school focuses on multiscale modelling of electrophysiology
and mechanics of the heart, and related material in computational
neurophysiology and pharmacology.
We are seeking master's and early doctoral students to participate and will
accept applications until February 1, 2026.
The summer school takes place in two blocks:
June 15-26: Simula Research Laboratory, Oslo, Norway- Lecture series, project
work
August 3-11: University of California San Diego, La Jolla, CA, USA, Project work,
guest lectures and final student presentations
There are no registration fees, and accommodation expenses for successful
applicants are covered. 10 ECTS credits through the University of Oslo. Details
regarding scheduling, logistics, core scientific material, and the application
process can be found on the course website:
https://www.simula.no/sscp
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From: Pablo Seleson selesonpd@ornl.gov
Date: January 08, 2026
Subject: Invitation to talk by Prof. Oskay (Vanderbilt) – Jan. 22, 2-3PM EST
Dear Colleagues,
I would like to invite you to attend an upcoming presentation:
“Quantum Computing Algorithms for the Finite Element Method”
The talk will be given by Prof. Caglar Oskay from Vanderbilt University as part
of the Oak Ridge National Laboratory (ORNL) Computational Mechanics
Seminar series.
The seminar will be held on Thursday, January 22, 2026, from 2:00 to 3:00 PM
EST.
A Microsoft Teams link is available at:
https://computmech.ornl.gov/seminars.html
Best Regards,
Pablo Seleson
-------------------------------------------------------
From: Patrick Farrell patrick.farrell@maths.ox.ac.uk
Date: January 06, 2026
Subject: Solving PDEs with Firedrake, Oxford, Mar 2026
I will give a 2.5-day training course on solving partial differential
equations with Firedrake in Oxford, March 18-20 2026. Firedrake
automates finite element simulation. Users write high level
mathematical code expressing their weak forms, boundary conditions and
solver strategies, and a high performance parallel implementation is
then generated and executed.
The tutorial is aimed at all levels, from MSc students to senior faculty and those
solving partial differential equations in industry. Only a basic
knowledge of finite elements is necessary, although of course more
background is useful.
The course will cover both the basics of solving stationary and
time-dependent problems, as well as various advanced topics like
geometric multigrid and p-multigrid solvers, high-order mesh
generation and adaptive mesh refinement with Netgen, nonlinear
problems, mixed formulations and block preconditioners, eigenvalue
problems, and adjoints.
Registration is £25. For details, please see
https://www.firedrakeproject.org/
tutorial_mar_26.html
This training event is kindly supported by the Collaborative Computational
Project on Data-centric Computational Mechanics and the Computational
Science Centre for Research Communities (CoSeC).
-------------------------------------------------------
From: Jemima Tabeart j.m.tabeart@tue.nl
Date: January 08, 2026
Subject: Hackathon: Data Assimilation in Firedrake, 8-10 April 2026, RAL UK
A hackathon to demonstrate and extend new variational data
assimilation (varDA) capability in Firedrake (https://
www.firedrakeproject.org) will take place at Rutherford Appleton
Laboratory, UK 8th - 10th April 2026. Recent advances in
Firedrake’s varDA capabilities allow DA researchers to easily
employ a wide range of PDEs and discretisations to test their work,
with simulation scientists gaining access to the gradients required
to adopt variational DA.
The goal of this hackathon is to provide
1) an introduction and demo to Firedrake aimed at new users.
2) discussions to gather input from the wider scientific community
about relevant test problems and future developments.
3) interactive sessions giving participants the opportunity to gain
hands-on experience and provide input for the VarDA-Firedrake
project.
This hackathon is for scientists with any level of
previous experience with either Firedrake or variational DA –
beginners and experts are equally welcome.
This event is supported
by a CoSeC fellowship and RAL, so registration is free (but
mandatory before 25th March 2026). Further information, including
the registration link, can be found at https://
www.numerical.rl.ac.uk/events/hackathon-data-assimilation-in-
firedrake/
Please direct any questions to j.m.tabeart@tue.nl
-------------------------------------------------------
From: Annika Lang annika.lang@chalmers.se
Date: January 08, 2026
Subject: 9 PhD positions. Chalmers and University of Gothenburg, Sweden
This year, we are recruiting 9 new PhD students at the Department
of Mathematical Sciences at Chalmers and the University of
Gothenburg:
- Link to an overview of all positions: https://
www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?
rmpage=job&rmjob=14489
- Application deadline: February 23, 2026
Two of the PhD positions might be of special interest to the NA
Digest community:
===
PhD position in computational mathematics
- Project: Time-evolving stochastic manifolds. The project includes
components of stochastic analysis, geometry, partial differential
equations (PDE), and computational mathematics.
- Link to
announcement and application system: https://www.chalmers.se/en/
about-chalmers/work-with-us/vacancies/?rmpage=job&rmjob=14482
- Supervisor: Annika Lang (annika.lang@chalmers.se)
- Application deadline: February 23, 2026
===
PhD position in Geometric
Hydrodynamics
- Project: within geometric hydrodynamics, using
modern differential geometry and computational mathematics for a
better understanding of partial differential equations describing
fluid-like phenomena in nature.
- Link to announcement and
application system: https://www.chalmers.se/en/about-chalmers/work-
with-us/vacancies/?rmpage=job&rmjob=14479
- Supervisor: Klas Modin
(klas.modin@chalmers.se)
- Application deadline: February 23, 2026
===
Please forward the announcement to relevant candidates. If you
have questions, do not hesitate to contact us.
-------------------------------------------------------
From: Jan Nordbotten jan.nordbotten@uib.no
Date: January 05, 2026
Subject: PhD position, Dept. of Mathematics, University of Bergen, Norway
The Department of Mathematics invites applications for a PhD Research Fellow in
Applied and Computational Mathematics. This is a 3-year position funded by the
University of Bergen, with the possibility of a 4th year dedicated to career
development (e.g., teaching experience).
You’ll be part of the Center for Sustainable Subsurface Resources (CSSR) – a
national research hub funded by the Norwegian Research Council. CSSR’s mission
is bold: develop cutting-edge digital solutions to drastically reduce Norway’s
offshore emissions. To support the goals of CSSR, this project aims to develop,
analyze and implement new nonlinear iterative solvers, with the goal of exploiting
models of various complexity, ranging from high-performance computing, via
reduced-order models to data-driven (machine-learned) representations. In
particular, we are interested in the joint applicability of such models and to what
extent simpler models (possibly based on machine learning) can be integrated
into full-physics simulation. Your research will directly contribute to this
transformative goal.
Your role:
-Develop and analyze nonlinear and linear solvers in the context of multi-model
analysis of and simulation of subsurface operations
- Build on a theoretical foundation from numerical and functional analysis
- Build on the literature related to linear operator preconditioning and nonlinear
preconditioners for Newton methods
- Use concrete model problems and numerical examples to guide and prototype
the development
For more information on the position and how to apply, please check out:
https://www.jobbnorge.no/en/available-jobs/job/292201/phd-research-fellow-in-
applied-and-computational-mathematics-cssr
-------------------------------------------------------
From: Fred Roosta fred.roosta@uq.edu.au
Date: January 03, 2026
Subject: PhD Opportunity in Mathematical Optimisation at The University of Queensland (Australia)
We are offering a fully funded PhD position in the School of Mathematics and
Physics at The University of Queensland, focused on the development and
analysis of next-generation Newton-type optimisation methods. The project
addresses fundamental questions in large-scale optimisation and numerical linear
algebra, with strong connections to modern machine learning.
Applicants should have a strong background in applied mathematics,
optimisation, linear algebra, or closely related areas, with experience in
programming (e.g. Python).
The position is supported by a competitive scholarship covering tuition fees and
a living stipend.
Further details and application instructions are available on the project webpage:
https://study.uq.edu.au/study-options/phd-mphil-professional-
doctorate/projects/next-generation-newton-type-methods-minimum-residual-
solver
-------------------------------------------------------
From: Tom Ranner T.Ranner@leeds.ac.uk
Date: January 05, 2026
Subject: PhD Opportunity in Numerical Analysis or Scientific Computing, University of Leeds
The School of Computer Science at the University of Leeds is
inviting applications from UK/Home-fee rated applicants for
two EPSRC DLA fully funded scholarships in any area of computer
science, including numerical analysis and scientific computation.
Start date: 1 Oct 2026 Duration: 3.5 years Fully funded
Application Deadline: Fri 30 Jan 2026
Apply/info:
https://phd.leeds.ac.uk/project/2357-epsrc-dla-scholarship-in-the-school-of-
computer-science
Informal enquiries can be addressed to:
Tom Ranner (T.Ranner@leeds.ac.uk)
-------------------------------------------------------
From: Jan Glaubitz jan.glaubitz@liu.se
Date: January 05, 2026
Subject: PhD opportunity in Bayesian Computational Mathematics, Linköping University, Sweden
We invite applicants for one fully funded PhD position (5 years) in Bayesian
Computational Mathematics under the supervision of Prof. Jan Glaubitz
(https://www.janglaubitz.com) at the Division of Applied Mathematics,
Linköping University, Sweden. The position includes research (80%) and
teaching (20%) in English and is compensated with a competitive salary and
high job security.
The research project is at the intersection of inverse problems, Bayesian
learning, and uncertainty quantification and will address fundamental questions
about trustworthy uncertainty quantification in science, engineering, and
machine learning.
For further details and to apply: https://liu.se/en/work-at-liu/vacancies/28185
Application deadline: March 2, 2026
Anticipated start date: Summer 2026 (flexible)
Contact: Please don't hesitate to contact Jan Glaubitz (jan.glaubitz@liu.se)
with any questions
I would be grateful if you could share this announcement with potential
candidates.
Best,
Jan Glaubitz
-------------------------------------------------------
From: Melina Freitag melina.freitag@uni-potsdam.de
Date: January 02, 2026
Subject: PhD and Postdoc postions in Data Assimilation at University of Potsdam
Several Doctoral and Postdoctoral positions are available within the SFB 1294
at the University of Potsdam and partner institutions.
The SFB 1294 is a collaborative research centre with focus on the mathematics
of data assimilation, with diverse application areas. For more information on
open positions and the application procedure, please visit
https://www.sfb1294.de/open-positions
-------------------------------------------------------
From: Andreas Frommer frommer@uni-wuppertal.de
Date: January 06, 2026
Subject: Postdoc position in Numerical Simulation for Lattice QCD at Wuppertal University
The Faculty of Mathematics and Natural Sciences at the University of
Wuppertal, Germany invites outstanding candidates to apply for a
two-year postdocl position
in the field of numerical simulations of lattice Quantum Chromodynamics
(QCD). The successful applicant will join project "Computing quark propagation
in a gluon background" of the Research Unit "Future methods for studying
confined gluons in QCD" (FOR 5269, https://for5269.desy.de/ ) funded by the
German Research Foundation (DFG). Research topics include algorithmic
developments for distillation, variance reduction in stochastic trace estimation
and GPU implementations. The appointment starts September 1st, 2026 and
ends August 31st, 2028.
A Masters (or comparable) degree and PhD degree in mathematics, informatics
or physics are required. Very good programming skills are a requirement and
familiarity with the research topics mentioned above is an advantage. Please
submit your application documents (CV, statement of research interests,3
letters of reference) by email to Andreas Frommer (frommer@uni-
wuppertal.de) who is also the contact for any further inquiries.
The deadline for application is January 30th, 2026.
-------------------------------------------------------
From: Nicola Guglielmi nicola.guglielmi@gssi.it
Date: January 04, 2026
Subject: Postdoctoral positions at Gran Sasso Science Institute, Italy
The Mathematics Area at the Gran Sasso Science Institute (GSSI) in L’Aquila,
Italy, is seeking highly qualified and motivated candidates for two postdoctoral
positions in Mathematics. The deadline for applications is January 12, 2026.
The total salary (gross of charges borne by the Institution) amounts to
€55,000.00. For further information, please do not hesitate to contact us at
phd.math@gssi.it.
The main research interests of the Mathematics Area at GSSI are: Analysis of
PDEs in classical and non-classical fluid mechanics, dispersive PDEs, hyperbolic
systems of conservation laws, pattern analysis, numerical linear algebra,
numerical methods for PDEs and dynamical systems, stochastic methods in
statistical mechanics, hydrodynamic limits, interacting many-body systems,
quantum macroscopic evolution equations, stochastic differential equations,
computational methods in fluid mechanics and turbulent flows, high-
performance computing, machine learning methods in computational
problems.
GSSI is a world-renowned research institute and school of advanced studies.
The Institute is located in L’Aquila, a culturally vibrant town in the centre of
Italy, with a low cost of living. It also hosts the University of L’Aquila and the
nearby INFN Gran Sasso National Laboratory. While widely appreciated for its
historical heritage and outdoor activities, the town has become an international
centre of attraction for its academic and research institutions.
All positions are research-oriented with no teaching duties.
For more information, please see the PDF of the Call on the following webpage.
https://www.mathjobs.org/jobs/list/27939
For questions and general inquiries, please contact us at applications@gssi.it.
-------------------------------------------------------
From: Lehel Banjai hod.maths@hw.ac.uk
Date: January 08, 2026
Subject: Assistant Professor position at Heriot-Watt University, Edinburgh
The Department of Mathematics, Heriot-Watt University, seeks to
appoint an Assistant Professor in Teaching and Research. The successful
candidate will play a leading role in our BSc Data Science and Software
Engineering joint programme with Xidian University in Xi’an, China. The
teaching on the programme is delivered in short blocks in China as well as at
our campus in Edinburgh.
The successful candidate will also be expected to produce high-quality
research, secure research funding, and supervise PhD and postdoctoral
students. While the research area is open, the ability to supervise bachelor’s
and master’s theses in the broad field of Data Science is essential.
The closing date for applications is Monday 2nd February 2026. For more
information and how to apply see:
https://enzj.fa.em3.oraclecloud.com/hcmUI/CandidateExperience/en/job/4606
Any questions about the post can be addressed to: Lehel Banjai
hod.maths@hw.ac.uk.
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: January 07, 2026
Subject: Contents, AIMS New Articles: JMD Vol. 21, Art. 20-22
Journal of Modern Dynamics
Volume: 21, Art. 20-22 2025
https://www.aimsciences.org/jmd/article/2025/21/0
Bumpy metric theorem in the sense of Mañé for non-convex Hamiltonians
Shahriar Aslani and Patrick Bernard
The 2022 Michael Brin Prize in Dynamical Systems
The Editors
On the work of Zhiren Wang on rigidity in dynamics
Ralf Spatzier
-------------------------------------------------------
From: Lothar Reichel reichel@math.kent.edu
Date: January 02, 2026
Subject: Contents, Electronic Transactions on Numerical Analysis (ETNA)
Contents, Electronic Transactions on Numerical Analysis (ETNA), vol. 61, 2024:
Special volume of the METT-X Workshop, Aachen, 2023.
Note: ETNA accepts software publications as well as
historical papers.
Preface, page vi
K. Lund and D. Palitta, Low-rank-modified Galerkin methods for the Lyapunov
equation, pp. 1-21
L. Grasedyck, M. Klever, and S. Kramer, Quasi-orthogonalization for
alternating non-negative tensor factorization, pp. 22-57
H. Bozorgmanesh, Relaxation of the rank-1 tensor approximation using
different norms, pp. 58-71
E. Begovic Kovac and L. Perisa, CP decomposition and low-rank approximation
of antisymmetric tensors, pp. 72-94
J. Saak and S. W. R. Werner, Using factorizations in Newton's method for
solving general large-scale algebraic Riccati equations, pp. 95-118
P. Kurschner, Inexact linear solves in the low-rank alternating direction
implicit iteration for large Sylvester equations, pp. 119-137
C. Bertram and H. Fassbender, A class of Petrov-Galerkin Krylov methods for
algebraic Riccati equations, pp. 138-162
O. Coulaud, L. Giraud, and M. Iannacito, A note on TT-GMRES for the solution
of parametric linear systems, pp.163-187
L. Grasedyck and T. A. Werthmann, Operator-dependent prolongation and
restriction for the parameter-dependent multigrid method using low-rank
tensor formats, pp. 188-207
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End of Digest
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