Today's Editor:
Alex Townsend
Cornell University
townsend@cornell.edu
Today's Topics:
Householder Award Recipients
Introducing the Mimetic Operators Library Enhanced (MOLE)
SciCADE 2026 (Edinburgh, June 29-July 3, 2026) Call for Minisymposia
From Modeling to Learning with HPC: ICERM Workshop, 13-14 Sep 2025
Summer School on Numerical Analysis, Jena, Germany, Aug 2025, deadline extended
Workshop on Energy-Efficient Computing, September 2025
Lecturer Position (12 months), University of Galway
Postdoc Fellowship Position in Artificial Intelligence, Brazil
PhD and PostDoc positions at TU Dresden, Germany
PhD Position in Optimization and Scientific Computing Using LBM, KIT, Germany
PhD Position in Numerical Analysis at Lund University
4 Fully Funded PhD Positions in High-Performance Scientific Computing – University of Pisa (Deadline: July 18)
Contents, AIMS New Volume: CAC Vol. 4
Contents, AIMS New Volume: CAC Vol. 5
Contents, AIMS New Volume: FMF Vol. 5
See this issue of NA Digest on the web at:
https://na-digest.coecis.cornell.edu/na-digest-html/25/v25n26.html
Submissions, FAQs, and archives:
https://na-digest.coecis.cornell.edu/
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From: Alan Edelman edelman@mit.edu
Date: June 26, 2025
Subject: Householder Award Recipients
The Householder Award XXII (2025) for the best dissertations in
numerical linear algebra for the period 2022–2024 has been awarded
jointly to:
Alice Cortinovis, now at the University of Pisa, for the dissertation
"Fast deterministic and randomized algorithms for low-rank
approximation, matrix functions, and trace estimation," written at the
École Polytechnique Fédérale de Lausanne (EPFL), Switzerland, under
the direction of Daniel Kressner.
Jorge Garza-Vargas, now at Caltech, and soon to be at Princeton
University (Fall 2025) and MIT (2026), for the dissertation "Rigorous
Guarantees for Randomized Diagonalization Algorithms," written at the
University of California, Berkeley, under the direction of Nikhil
Srivastava.
Jess Banks Vine, now working with the United Auto Workers union, for
the dissertation "Random Matrices and Provable Algorithms for
Approximate Diagonalization," also written at the University of
California, Berkeley, and also under the direction of Nikhil
Srivastava.
The awards were presented at a banquet during the Householder
Symposium XXII in Ithaca, NY, on June 11, 2025.
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From: Jose E. Castillo jcastillo@sdsu.edu
Date: June 21, 2025
Subject: Introducing the Mimetic Operators Library Enhanced (MOLE)
MOLE is an open-source library for high-order mimetic operators, offering
discrete analogs of core vector calculus operators: divergence, gradient, curl,
and Laplacian. These act on functions defined over staggered grids—uniform,
nonuniform, or curvilinear—and uphold both local and global conservation laws.
MOLE’s operators serve as foundational tools for building efficient
computational schemes for the solution of partial differential equations (PDEs).
Last summer, through the NSF POSE program, we interviewed some of you,
over sixty current and potential MOLE users, who helped us identify areas for
library enhancement and high-impact features. Since then, the core team and
contributors have implemented top-ranked improvements aligned with the NSF
Open Source Ecosystem project goals. Key updates include expanded
technical and community documentation, new C++ examples, and the adoption
of modern development workflows, such as automated builds, full unit test
coverage, and boundary condition support, which are critical for users working
in periodic domains. We are establishing an Open Source Ecosystem to
sustainably maintain MOLE’s reliability, extensibility, robustness and, availability.
Read the latest:
https://mole-docs.readthedocs.io/en/latest/
We’d love your feedback—please take a look and let us know what you think.
—The MOLE Team
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From: Benedict Leimkuhler b.leimkuhler@ed.ac.uk
Date: June 26, 2025
Subject: SciCADE 2026 (Edinburgh, June 29-July 3, 2026) Call for Minisymposia
SciCADE (Scientific Computing and Differential Equations) is a long-running
conference series that promotes work in scientific computing and differential
equations, including theoretical, algorithmic, numerical analysis and
applications aspects. In 2026, the SciCADE conference will be held in
Edinburgh, UK, June 29-July 3. The plenary talks at the meeting will be given
by Patrick Farrell (Oxford), Tammy Kolda (MathSci.ai), Buyang Li (Hong Kong
Polytechnic), Weiqing Ren (National University of Singapore), Jesus-Maria
Sanz-Serna (Universidad Carlos III, Madrid), Aretha Teckentrup (Edinburgh
University), Xiaochuan Tian (University of California at San Diego) and Richard
Turner (Cambridge). For the 2026 meeting we highlight a wide range of topics
addressing numerical methods, computational science, data science, machine
learning and AI foundations, high performance computing, statistical
computation, and applications (in finance, climate, biology and fluids); please
see the scicade website at www.scicade.org for a full list of interest areas. In
addition to the conference, we intend to hold a summer school for graduate
students and other early-career researchers in the week preceding the
meeting; this will be announced soon on the conference website.
On our website, you will find information about the history and aims of the
meeting, the speakers (with links to their web pages), sponsorship and key
dates. There is also a link to a form where you are invited to propose a
minisymposium at the meeting. A typical minisymposium will consist of four
related talks on some central theme relevant to the meeting. A double session
(eight talks) may also be proposed. The call for minisymposia formally closes
on January 15, 2026, but we intend to accept and announce some
minisymposia early.
Please join us in Edinburgh next year for this exciting event!
Organizing Committee (from Edinburgh and Heriot-Watt universities):
Lehel Banjai, Emmanuil Georgoulis, Desmond Higham, Kaibo Hu, Stefan Klus,
Benedict Leimkuhler, John Pearson, Mariya Ptashnyk, Aretha Teckentrup,
Kostas Zygalakis
Scientific Committee:
Weizhu Bao (Singapore), Qiang Du (Columbia), Erwan Faou (Rennes), Benedict
Leimkuhler (Edinburgh), Melvin Leok (San Diego), Christian Lubich (Tübingen),
Alexander Ostermann (Innsbruck), Linda Petzold (Santa Barbara), Tao Tang
(Hong Kong), Carol Woodward (Livermore)
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From: David Keyes david.keyes@kaust.edu.sa
Date: June 20, 2025
Subject: From Modeling to Learning with HPC: ICERM Workshop, 13-14 Sep 2025
Applications are open for a workshop “From Modeling to Learning with
HPC” at the Institute for Computational and Experimental Research in
Mathematics (ICERM), Brown University, Providence, RI, 13-14 September
2025 at
https://icerm.brown.edu/program/hot_topics_workshop/htw-25-mlhpc.
Demands of resolution and fidelity have driven the performance of
simulations of first-principles mathematical models in science and
engineering from MegaFlop/s to ExaFlop/s and their datasets from
MegaBytes to ExaBytes (12 orders of magnitude) over the past four
decades. Over the most recent decade, the application of machine
learning to science and engineering systems has created a similar
demand for performance and associated storage. Lower levels of the
software stack created for simulation have proved immediately useful
for machine learning at scale. However, higher levels of the
simulation software have not yet fulfilled their potential to lift the
dominant algorithms for machine learning and inference today above
relatively “brute force” implementations, resulting in massive costs
for facilities and energy that slow progress and restrict access to
the research frontier for many. At the same time, hardware optimized
for machine learning applications possesses yet unrealized potential
for traditional simulation. Increasingly, the same science or
engineering application is more effectively addressable by simulation
and learning working in tandem than by either alone, resulting in a
confluence of two formerly distinct research communities. This “hot
topics” weekend workshop aims to capitalize by highlighting
opportunities for cross-fertilization in both directions.
The mission of ICERM, core-funded by the US National Science
Foundation, with significant program funding from the Simons
Institute, is to support and broaden the relationship between
mathematics and computation. This Hot Topics workshop coincides with
the 70th birthday of Professor William Gropp, Director of the NSF
National Center for Supercomputer Applications (NCSA) and will
commemorate his profound contributions to high performance computing
in simulation, big data, and machine learning.
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From: Dietmar Gallistl NAschool25@uni-jena.de
Date: June 23, 2025
Subject: Summer School on Numerical Analysis, Jena, Germany, Aug 2025, deadline extended
The Summer School on Numerical Analysis will take place from 19. to
21. August 2025 at U Jena, Germany. The speakers are Michael Feischl
(TU Wien) on "Optimal approximation for low and high dimensional
problems" and André Uschmajew (U Augsburg) on "Tensors and numerical
multilinear algebra".
The registration deadline has been extended:
Registration is free but mandatory. All relevant information can be
found under https://numerik.uni-jena.de/summerschool
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From: Hussam Al Daas hussam.al-daas@stfc.ac.uk
Date: June 23, 2025
Subject: Workshop on Energy-Efficient Computing, September 2025
The Computational Mathematics Group from STFC's Scientific Computing
Department (https://www.numerical.rl.ac.uk/) is organising a workshop on
Energy-Efficient Computing. The workshop will take place at the Rutherford
Appleton Laboratory near Oxford on 15-16 September 2025. All are very
welcome to attend, but registration is mandatory. There is no registration fee
for attendance - registration DEADLINE: 1st September 2025. Please register
using this registration form:
https://web.cvent.com/event/82dea400-abc9-439a-81bb-
dd4dd634f03d/summary
The 2-day workshop is primarily aimed at software development teams
embedded within CoSeC communities (https://www.cosec.ac.uk/) but is also
suitable for wider audiences. The sessions will revolve around four key
themes: Qualitative Algorithms, Community, Hardware, and Quantitative
Practice and will be designed to share knowledge and start conversations
around making energy-efficient choices.
List of confirmed speakers:
- Grey Ballard (Wake Forest University, USA)
- Laura Grigori (EPFL - PSI, Switzerland)
- Martin Juckes (STFC, UK)
- Loic Lannelongue (University of Cambridge, UK)
- Hatem Ltaief (KAUST, KSA)
- Théo Mary (LIP6, Sorbonne University, France)
- Kirsty Pringle (Software Sustainability Institute, The University of Edinburgh,
UK)
- Andy Turner (EPCC, University of Edinburgh, UK)
- Michèle Weiland (EPCC, University of Edinburgh, UK)
- Garth Wells (Cambridge University, UK)
Further details can be found at:
https://www.numerical.rl.ac.uk/events/workshop-on-green-computing/
-------------------------------------------------------
From: Niall Madden Niall.Madden@UniversityOfGalway.ie
Date: June 25, 2025
Subject: Lecturer Position (12 months), University of Galway
Applications are invited for an appointment as Lecturer in Mathematics (full
time, fixed-term for 12 months) in the School of Mathematical and Statistical
Sciences, University of Galway. This is a Contract Type B post, meaning that
research and teaching have equal focus.
Applications from mathematicians with experience of teaching and research
in any area of mathematics (including Numerical Analysis and Scientific
Computing) will be considered. However, we are particularly eager to recruit
a lecturer who can contribute to teaching Financial Mathematics and/or
Actuarial Science.
Salary €63,624-€101,498. p.a., depending on experience.
For informal enquiries, contact Dr Niall Madden, Email:
Niall.Madden@UniversityOfGalway.ie
For more, see https://www.universityofgalway.ie/human-
resources/links/011134acad/
Closing date for applications is 17:00 (Irish Time) on 10th July 2025.
-------------------------------------------------------
From: Reference Center for Artificial Intelligence (CEREIA) diretoria.cria@ufc.br
Date: June 26, 2025
Subject: Postdoc Fellowship Position in Artificial Intelligence, Brazil
The Reference Center for Artificial Intelligence (CEREIA), a Research Center based
at Federal University of Ceará in Brazil, is offering a postdoctoral fellowship in
Artificial Intelligence. This program offers an exciting opportunity for early-career
researchers to advance their academic and research careers in the dynamic field
of AI. CEREIA is committed to promoting excellence in AI research, with specific
focus on addressing healthcare-related problems and challenges. CEREIA
conducts several projects, including prediction of chronic diseases; engagement
of patients in health promotion and chronic disease prevention programs;
intelligent systems for remote patient monitoring; analysis and processing of
medical images; medical history assisted by artificial intelligence; and others.
The position is a two-years contract funded by the São Paulo Research
Foundation (FAPESP). In general, fellowship recipients collaborate in research
under the supervision of one or more Center’s members for two years. The
fellowship may be extended for an additional year, depending on performance
and availability of funds.
Applications are due July 18th, 2025 (late submissions will not be considered).
Please see the Announcement for more information:
https://cria.ufc.br/en/2025/06/26/international-public-selection-for-postdoctoral-
fellowship-in-ai-2/
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From: Axel Voigt axel.voigt@tu-dresden.de
Date: June 24, 2025
Subject: PhD and PostDoc positions at TU Dresden, Germany
At the Faculty of Mathematics at the Institute of Scientific Computing and
within the Dresden Center for Computational Materials Science (DCMS), two
positions are available at the earliest possible date as Research assistant /
PhD student or Postdoc (E 13TV-L) for a period of three years. The positions
are embedded in the activities of the project “Analyzing structure-property
relations in equilibrium and non-equilibrium hyperuniform systems”,
coordinated by Prof. Dr. Marco Salvalaglio and Prof. Dr. Axel Voigt and funded
by the German Research Foundation (DFG). The core activities will focus on
the investigation of disordered correlated systems using various tools and
models, including: i) characterization of the emerging patterns in physical
systems (solid state materials and active systems); ii) investigation of the
mechanical properties and the effects of disordered correlated
microstructures on diffusion; iii) development of energy-based models and
numerical simulations of hyperuniform assemblies; iv) development and
application of techniques for the analysis of topological data. Tasks:
• Generation of hyperuniform patterns (point, scalar and vector fields)
• Application of topological data analysis tools such as persistent
homology and graph statistics
• Development of special phase field and phase field crystal models
• Coupling newly developed approaches with established approaches for
simulating e.g. mechanical properties and the flow of fluids
• Implementation of models in existing simulation software
• Conducting numerical studies, also on HPC systems.
Requirements:
• scient. university degree (e.g. Master's, Diploma) in mathematics,
physics, materials science or related subjects
• Basic knowledge of computer programming (e.g. Python, Matlab and
C++)
• Excellent knowledge of the English language
• strong problem-solving skills, motivation/interest in scientific research,
willingness to learn and work in a group
• Applications with proof of previous experience with numerical
methods/simulations, state-of-the-art computational techniques (e.g. data-
driven methods and/or FEM) and/or theoretical material modeling will be
given preference
We offer:
• Opportunity to collaborate with internationally renowned researchers in
the field of research
• Participation in exchange programs and short research stays abroad
• Extensive range of further education and training opportunities
• Flexible working hours and mobile working arrangements for a good
work-life balance
• Job ticket for public transportation
Please submit your detailed application with the usual documents by July
31st 2025 to axel.voigt@tu-dresden.de.
-------------------------------------------------------
From: Mathias J Krause mathias.krause@kit.edu
Date: June 25, 2025
Subject: PhD Position in Optimization and Scientific Computing Using LBM, KIT, Germany
Open Position: Research Assistant (Doctoral Student) in Optimization
and Scientific Computing Using Lattice Boltzmann Methods
At the Institute of Applied and Numerical Mathematics (IANM) at the
Karlsruhe Institute of Technology (KIT) we are looking for a
Research Assistant (f/m/d)
for our team Lattice Boltzmann Research Group (LBRG,
http://www.lbrg.kit.edu). The position is part of an exciting research
project focused on advanced numerical modelling and simulation with
focus on sensitivity analysis and optimization for fluid dynamics,
solid mechanics, and fluid-structure interaction (FSI) using lattice
Boltzmann methods (LBM). After familiarisation, remuneration is paid
according to TV-L, E 13. This role provides the opportunity to pursue
a doctorate (PhD degree).
Your Responsibilities:
• Development and implementation of efficient and scalable LBM
algorithms for complex multi-physics problems, specifically in OpenLB
(www.openlb.net)
• Development and application of adjoint-based and data-driven
optimization methods
• High-performance computing (HPC) on modern GPU-accelerated architectures
• Scientific collaboration with internal and external partners
• Participation in teaching and supervision of students
• Presentation of results at international conferences and publication
in peer-reviewed journals
Your Profile:
• Master’s degree (or equivalent) in applied mathematics, scientific
computing, or a related field
• Strong background in optimization, numerical methods and scientific
computing
• Experience in fluid dynamics, solid mechanics, or LBM is highly
advantageous
• Programming skills in C/C++ or similar
• Experience with parallel computing is a plus
• Curiosity, creativity, and a collaborative mindset
• Very good written and spoken English skills; basic German skills
We Offer:
• An inspiring research environment in a dynamic and interdisciplinary
research group at one of Europe’s leading technical universities
• Structured doctoral support and career development
• A vibrant campus life in the heart of Karlsruhe
Application:
Please send your application including a cover letter, CV,
transcripts, and contact details of at least one reference as a single
PDF file to:
PD Dr. Mathias J. Krause
Karlsruhe Institute of Technology
Lattice Boltzmann Research Group
Street at Forum 8
76131 Karlsruhe
e-mail: mathias.krause@kit.edu
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From: Mengwu Guo mengwu.guo@math.lu.se
Date: June 26, 2025
Subject: PhD Position in Numerical Analysis at Lund University
We are calling for applications for one or two PhD positions at Lund University's
Centre for Mathematical Sciences to work in the doctoral program subject
Numerical Analysis.
The research project lies at the intersection of numerical analysis and scientific
machine learning. It aims to build a mathematically grounded approach for
approximating PDEs using deep kernel learning, which integrates deep neural
networks into Gaussian processes constrained by PDEs. Drawing on tools from
numerical analysis and reproducing kernel Hilbert space theory, the project
seeks to rigorously embed physical laws into deep learning while enabling
uncertainty quantification and error estimation. This project is supported by the
Wallenberg AI, Autonomous Systems and Software Program (WASP) in
Sweden, and the successful candidate(s) will join the WASP graduate school.
Please refer to the job application portal on Varbi
(https://lu.varbi.com/en/what:job/jobID:837453/iframeEmbedded:0/where:4) for
further descriptions and application guidelines. Interested candidates are
welcome to send an application through Varbi by August 1, 2025.
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From: Fabio Durastante fabio.durastante@unipi.it
Date: June 24, 2025
Subject: 4 Fully Funded PhD Positions in High-Performance Scientific Computing – University of Pisa (Deadline: July 18)
Dear colleagues,
We are glad to announce that the University of Pisa has launched a new
interdisciplinary industrial PhD program in High-Performance
Scientific Computing (HPSC) with 4 fully funded positions open for
applications (EU and non-EU), starting November 2025.
This innovative doctoral program is designed in collaboration with the
medical technology company Sordina IORT Technologies, and brings
together 8 university departments and several national research
institutes. It focuses on the development of advanced computational
methods and HPC-based solutions for complex problems in science,
engineering, and medicine.
Specific research topics for the funded scholarships include:
- Iterative Methods and Preconditioners for Sparse Linear Systems on
Pre-Exascale and Exascale Architectures
- HPC Software for Design and Analysis of Electronic Devices using
Advanced Materials and AI/ML
- Computational Models for Flash Radiotherapy and Radiobiological
Applications (2 positions)
- Reduced-Precision and Matrix Units on AI GPUs for Efficient
Solution of the Wave Equation
The program offers a unique interdisciplinary environment where PhD
candidates will develop expertise in:
- Numerical algorithms and scientific computing
- HPC architectures and parallel programming
- AI/ML techniques applied to physical and biomedical systems
- Application domains such as climate modeling, advanced materials,
and smart medical technologies
This is an industrial PhD: selected candidates will have the
opportunity to work closely with Sordina IORT Technologies on
translational research projects in medical computing and radiotherapy,
ensuring both academic excellence and real-world impact.
Application deadline: July 18, 2025
Program website and full call: https://www.dm.unipi.it/phd-hpsc/
We welcome applications from outstanding Master’s graduates in
mathematics, computer science, physics, engineering, chemistry, and
related fields.
Please feel free to circulate this announcement to your students,
collaborators, and relevant mailing lists.
With best regards,
Fabio Durastante
University of Pisa
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From: Charley Denton cdenton@aimsciences.org
Date: June 24, 2025
Subject: Contents, AIMS New Volume: CAC Vol. 4
Communications on Analysis and Computation
Volume: 4
2025
https://www.aimsciences.org/CAC/article/2025/4/0
Strong convergence of Lévy-driven mixed stochastic integro-differential
equations with application to the rough mixed volatility models
Zhaoqiang Yang and Chenglong Xu
Proportional armament model and its analysis on time scales
Zehra Özdemir and Emrah Yilmaz
The anisotropic interior transmission eigenvalue problem with a conductive
boundary
Victor Hughes, Isaac Harris and Jiguang Sun
Hessian quotient equations on exterior domains
Haigang Li, Xiaoliang Li and Shuyang Zhao
High-frequency stability estimates for the linearized inverse boundary value
problem for the polyharmonic operator with constant attenuation
Anupam Pal Choudhury and Ajith Kumar T
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From: Charley Denton cdenton@aimsciences.org
Date: June 24, 2025
Subject: Contents, AIMS New Volume: CAC Vol. 5
Communications on Analysis and Computation
Volume: 5
2025
https://www.aimsciences.org/CAC/article/2025/5/0
A monotonicity-based globalization of the level-set method for inclusion
detection
Bastian Harrach and Houcine Meftahi
Simultaneous estimation of piecewise constant coefficients in elliptic PDEs via
Bayesian level-set methods
Anuj Abhishek, Thilo Strauss and Taufiquar Khan
Using the Newton-Raphson Method with Automatic Differentiation to
Numerically Solve the Implied Volatility of Stock Options via the Binomial Model
Wanchaloem Wunkaew, Yuqing Liu and Kirill V. Golubnichiy
-------------------------------------------------------
From: Charley Denton cdenton@aimsciences.org
Date: June 24, 2025
Subject: Contents, AIMS New Volume: FMF Vol. 5
Frontiers of Mathematical Finance
Volume: 5
2025
https://www.aimsciences.org/FMF/article/2025/5/0
Capital structure and risk acceptability
Dilip B. Madan, Yoshihiro Shirai and King Wang
Portfolio optimization in a multivariate jump-diffusion model
Dominik de Witte, Jan-Frederik Mai and Matthias Scherer
The term structure of implied correlations between S&P and VIX markets
Laura Ballotta, Ernst Eberlein and Grégory Rayée
Filtration reduction and completeness in Brownian motion models
Karen Grigorian and Robert A. Jarrow
Occupation time, quantile and rank of the Ornstein–Uhlenbeck process and their
applications to mathematical finance
Yuri Imamura, Takashi Kato, Ryozo Miura and Ju-Yi Yen
Efficient inverse Z-transform and pricing barrier and lookback options with
discrete monitoring
Svetlana Boyarchenko and Sergei Levendorskiĭ
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End of Digest
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