From bounce-5434511-88629717@mm.list.cornell.edu Fri May 15 08:22:13 2026 From: "Alex John Townsend" Subject: NA Digest, V. 26, # 20 Date: Fri, 15 May 2026 08:20:29 -0400 NA Digest Friday, May 15, 2026 Volume 26 : Issue 20 Today's Editor: Alex Townsend Cornell University townsend@cornell.edu Today's Topics: Announcing the release of MOLE v1.2 New Book, Perturbation Methods Using Backward Error MFEM Community Workshop Sep 22-25, 2026 Workshop on Optimization with Differential Equations, Wuerzburg, Sept 16-18 2026 PhD position in Scientific Machine Learning (SciML) in FEMTO-ST, France PhD Position (3 years) in Applied Mathematics -- University of Oulu, Finland PhD Position: Error Propagation and Implicit Priors, DTU, Denmark 5 PhD Positions in High Performance Scientific Computing -- University of Pisa PhD and Postdoc position in Mathematics at Strathclyde University Postdoc position in Numerical Linear Algebra at University of Leicester Assistant Professor in High-performance Computing at Trinity College Dublin Contents, AIMS New Article: ACSE Vol. 8, Art. 3 Contents, AIMS New Articles: CAC Vol. 9, Art. 1, 3 Contents, AIMS New Article: FAM Vol. 1, Art. 4 Contents, AIMS New Article: MFC Vol. 13, Art. 1 Call for papers, Springer Künstliche Intelligenz special issue AI4Science Call for papers: Special Issue of the Journal Numerical Algorithms on the occasion of the 65th anniversary of Nicola Mastronardi See this issue of NA Digest on the web at: https://na-digest.coecis.cornell.edu/na-digest-html/26/v26n20.html Submissions, FAQs, and archives: https://na-digest.coecis.cornell.edu/ ------------------------------------------------------- From: Jose E Castillo jcastillo@sdsu.edu Date: May 08, 2026 Subject: Announcing the release of MOLE v1.2 We are thrilled to announce a new release of The MOLE 1.2 library. The MOLE Open-source Ecosystem implements high-order mimetic operators in different programming languages. MOLE provides discrete analogs of the most common vector calculus operators: Divergence, Gradient, Curl, and Laplacian. These operators act on functions discretized over staggered grids (uniform, nonuniform, and curvilinear), and they satisfy local and global conservation laws. MOLE's operators can be used to develop computationally efficient programs for solving linear and nonlinear partial differential equations (PDEs) with higher orders of accuracy than other methods. Visit the MOLE website at https://mole-ose.org. For MOLE library documentation visit: mole-docs.readthedocs.io/. To report any issues, please create a GitHub Issue on the MOLE library repository https://github.com/csrc-sdsu/mole ------------------------------------------------------- From: Mitch Graham mgraham@siam.org Date: May 12, 2026 Subject: New Book, Perturbation Methods Using Backward Error Perturbation Methods Using Backward Error by Robert M. Corless and Nicolas Fillion "Corless and Fillion have written the rare book that bridges mathematical practice, computation, and philosophy. Perturbation Methods Using Backward Error brings new unity and rigor to a venerable subject, showing how backward error analysis can illuminate every corner of approximation -- from asymptotics and differential equations to computer algebra and modern numerical methods. Clear, concrete, and historically grounded, it captures both the beauty and the practicality of perturbation theory. Personally, I can't wait to teach from it -- and to keep learning from it." -Steven Strogatz, Cornell University Perturbation methods are old but powerful, and they remain in widespread use. Rather than producing numbers or pictures, they yield formulas whose value depends on the skill of the person (or machine!) interpreting them. This unique book presents several classical methods for solving perturbation problems. To ensure a uniform presentation and more reliable, interpretable results, it consistently uses backward error analysis. This provides a systematic way to assess the validity of approximate solutions while encouraging the modeler to examine how small changes in the data or model affect the result. To support this, the book uses the concept of a condition number, familiar from numerical analysis. Perturbation Methods Using Backward Error includes a chapter on the relatively novel renormalization group method, uses computer algebra (via Maple) to ease the computing of symbolic answers, provides solutions to all exercises, and discusses the impact on science of the idea of perturbation. 2026 / 443 pages / Softcover / 978-1-61197-885-8 / List $81.00 / SIAM Member $56.70 / MM25 Bookstore link: https://epubs.siam.org/doi/book/10.1137/1.9781611978865 ------------------------------------------------------- From: Qi Tang qtang@gatech.edu Date: May 13, 2026 Subject: MFEM Community Workshop Sep 22-25, 2026 The MFEM team and Georgia Tech's School of Computational Science and Engineering invite you to the 2026 MFEM Community Workshop, Sep 22-25 at Georgia Tech, with a virtual attendance option. Sep 22 will feature a hands-on MFEM tutorial. Register by Sep 11: https://forms.gle/sGtQrPFAMrgN1Kp59 In-person attendance fees: $150 (regular), $75 (students) For full details, please visit https://mfem.org/workshop Program highlights: - Free tutorial with separate registration (Sep 22): https://rb.gy/1w59h4 - Hybrid: Georgia Tech or Webex - Ideal for new users - Project news and roadmap - Developer talks (submit abstract with registration) - Student lightning talks (submit your abstract) - In-person poster session (submit your abstract) - Visualization contest (submit your images/animations) - Office hours We look forward to engaging with you at the workshop! ------------------------------------------------------- From: Daniel Wachsmuth daniel.wachsmuth@uni-wuerzburg.de Date: May 11, 2026 Subject: Workshop on Optimization with Differential Equations, Wuerzburg, Sept 16-18 2026 Annual workshop of the GAMM Activity Group on Optimization with Partial Differential Equations. This workshop brings together researchers working on optimization problems constrained by partial differential equations. It provides a forum for exchanging new results and fostering collaboration across analysis, numerical methods, and applications. Contributions from all areas of PDE‑constrained optimization are welcome. Invited speakers: Alberto de Marchi (University of the Bundeswehr Munich, Germany) Carmen Gräßle (TU Braunschweig, Germany) Philipp Guth (Austrian Academy of Sciences, Austria) Johannes Haubner (University of Graz, Austria)­ More information can be found on the website: https://www.mathematik.uni-wuerzburg.de/en/schools/optimization- with-partial-differential-equations/ Registration is open until July 24th. Looking forward to see you in Wuerzburg! Daniel Wachsmuth ------------------------------------------------------- From: Karim Cherifi karim.cherifi@supmicrotech.fr Date: May 11, 2026 Subject: PhD position in Scientific Machine Learning (SciML) in FEMTO-ST, France I'm happy to share that we are recruiting a fully funded PhD student at FEMTO- ST Institute and SUPMICROTECH, co-supervised by Jean-Julien Aucouturier and myself. Location: Besançon, France Start date: September 2026 (flexible) Duration: 3 years Application deadline: June 15, 2026 PhD Topic: Hard and Soft Constraints in Scientific Machine Learning The project focuses on one of the key challenges in Physics-Informed and Scientific Machine Learning: "How should physical constraints be integrated into machine learning models?" The research will involve: - Physics-informed ML and system identification - Dynamical systems and port-Hamiltonian formulations - Benchmarking constrained learning methods with applications in soft robotics and neuroscience The position is ideal for candidates with a strong background in: - Machine Learning - Control Theory - Applied Mathematics and Scientific Computing Strong Python/ML programming skills and prior research experience are highly appreciated. To apply, candidates should send: a CV, Cover letter and References to: karim.cherifi (at) supmicrotech.fr with the Subject: [PhD position] Your Name Please feel free to share this opportunity with interested students and researchers in SciML, control, and physics-informed AI communities. ------------------------------------------------------- From: Babak Maboudi Afkham babak.maboudi@oulu.fi Date: May 11, 2026 Subject: PhD Position (3 years) in Applied Mathematics -- University of Oulu, Finland The University of Oulu is inviting applications for a fully funded 3-year PhD position in Applied Mathematics within the project: "Sparse Measurement Strategies for Goal-Oriented Inverse Problems" The project is part of the SPARSe Academy Fellowship project and connected to the Finnish FAME Flagship (Flagship of Advanced Mathematics for Sensing, Imaging and Modelling). Research topics include: -inverse problems -uncertainty quantification -Bayesian methods -numerical analysis and scientific computing -PDE-based computational modelling -sparse and optimal measurement strategies Applications involve medical imaging, X-ray computed tomography, and seismic imaging. The position offers: - an active international research environment in inverse problems and computational mathematics - opportunities for international collaboration and yearly academic visits - participation in leading conferences in applied mathematics and inverse problems - access to national high-performance computing infrastructure - opportunities to contribute to open-source scientific software We welcome applicants with a strong background in applied mathematics, numerical analysis, scientific computing, PDEs, inverse problems, probability, optimization, or related areas. Application deadline: June 1, 2026 Further details and application: https://www.linkedin.com/feed/update/urn:li:activity:7459508958647508992 Informal inquiries are welcome: Babak Maboudi Afkham babak.maboudi@oulu.fi ------------------------------------------------------- From: Per Christian Hansen pcha@dtu.dk Date: May 11, 2026 Subject: PhD Position: Error Propagation and Implicit Priors, DTU, Denmark The Technical University of Denmark has an opening for a 3-year PhD position. It is part of the project DUDE, Data Uncertainty and Design/ Reconstruction Errors, headed by Prof. Per Christian Hansen. This position focuses on analysis of the influence of data errors in iterative solvers for inverse problems such as computed tomography and image deblurring. The goal is to establish a solid understanding of how data errors propagate in iterative regularization methods, especially CGLS and GMRES. In addition, we aim to interpret these methods in the framework of computational uncertainty quantification. For more details and to apply: https://efzu.fa.em2.oraclecloud.com/hcmUI/CandidateExperience/en/sites/CX_2001/job/7344/ The applicants will work together with two postdocs in the Section for Scientific Computing. Applicants will make limited contributions to teaching/training activities and supervision of students. The deadline of applications is June 10, 2026, at 23:59 (Danish time). ------------------------------------------------------- From: Luca Heltai luca.heltai@unipi.it Date: May 14, 2026 Subject: 5 PhD Positions in High Performance Scientific Computing University of Pisa Applications are now open for the 42nd cycle of the PhD programme in High Performance Scientific Computing (HPSC) at the University of Pisa. The programme focuses on advanced methods and technologies for scientific computing, including: - numerical methods for PDEs and multiphysics problems, - high performance computing and parallel algorithms, - scientific machine learning and AI for computational science, - large-scale simulation and optimization, - uncertainty quantification and data-driven modeling. The PhD is strongly interdisciplinary and involves collaborations with academic departments, research centers, and industrial partners. Several projects are directly connected to real-world HPC applications in engineering, climate science, biomedical modeling, computational physics, and related areas. The programme is aimed at students interested in research at the intersection of numerical analysis, scientific computing, and advanced computational technologies. Additional information, application deadlines, and the official call are available here: https://www.dm.unipi.it/phd-hpsc/call-for-applications-to-the-ph-d-programme-in-hpsc-42nd-cycle/ Please feel free to circulate this announcement to potentially interested students and collaborators. ------------------------------------------------------- From: Debasish Das debasish.das@strath.ac.uk Date: May 11, 2026 Subject: PhD and Postdoc position in Mathematics at Strathclyde University Applications are invited for two positions in the Department of Mathematics and Statistics at the University of Strathclyde, Glasgow: - A fully funded three-year PhD position open to international students - A three-year PDRA position These positions are supported by the Leverhulme Trust and focus on the mathematical and computational modelling of electrically driven helical microswimmers and related active matter systems. The PhD project will involve theoretical and computational work, including asymptotic methods, hydrodynamics, and the modelling of propulsion and interactions in viscous flows. International students are welcome to apply. The PDRA position will concentrate on high-fidelity numerical simulations of self-propelled helices and related active matter systems in three-dimensional fluids. Please feel free to share this post with anyone who may be interested. Further details are available here: https://lnkd.in/eV-Fkd29 PhD application: https://www.strath.ac.uk/studywithus/ postgraduateresearchphdopportunities/science/mathematicsstatistics/ activeself-propelledhelices/ PDRA application: https://strathvacancies.engageats.co.uk/ Vacancies/I/6585/0/468090/15019/postdoctoral-research-associate-in- applied-and-computational-mathematics-814375 ------------------------------------------------------- From: Behnam Hashemi b.hashemi@leicester.ac.uk Date: May 13, 2026 Subject: Postdoc position in Numerical Linear Algebra at University of Leicester Application deadline: Tuesday, 2 June 2026 Interviews: Late June or early July 2026 Start date: 1 August 2026 Contract: Fixed-term until 31 May 2029 A Postdoctoral Research Associate position is available to work with Dr Behnam Hashemi on the EPSRC-funded New Investigator Award Project, Rigorous Numerics for Transcendental Functions of Matrices. The project aims to develop verified algorithms for computing matrix functions with applications to monitoring the quality of results produced by standard floating-point algorithms and to computer-assisted mathematical proofs in dynamical systems and ordinary and partial differential equations. The role will involve developing rigorous a posteriori forward error bounds for matrix functions using interval analysis, as well as contributing to open- source software development in MATLAB and Python. The successful candidate will join the Scientific Computing and Applications Research Group in the School of Computing and Mathematical Sciences and will have opportunities to collaborate with project partners in Germany and the UK. Applicants should have a PhD in Mathematics or a closely related field, together with a strong track record in research and publication. Relevant expertise includes numerical linear algebra, floating-point arithmetic, interval arithmetic and dynamical systems. Excellent communication and presentation skills are required. For informal enquiries, please contact Dr. Behnam Hashemi at b.hashemi@le.ac.uk. Application URL: https://jobs.le.ac.uk/vacancies/13255/research-associate-in-rigorous-numerics-for-matrix-functions.html ------------------------------------------------------- From: Kirk M Soodhalter soodhalk@tcd.ie Date: May 08, 2026 Subject: Assistant Professor in High-performance Computing at Trinity College Dublin Dear colleagues, The School of Mathematics at Trinity College Dublin is inviting applications for the post of Assistant Professor in High-performance Computing. The appointment will be tenable from January 2027. This is a teaching and research position; the successful candidate will be required to contribute at all levels of teaching and supervision undertaken by the School and will be expected to conduct a vigorous research programme. Further details about the position can be found at https://my.corehr.com/pls/trrecruit/erq_jobspec_details_form.jobspec?p_id=038968 while the closing date for applications is July 22nd, 2026. I paste a blurb from the job description below the closing salutation. Informal enquiries can directed to headmath@maths.tcd.ie . Please bring this position to the attention of any potentially interested candidates. Sincerely, Kirk M Soodhalter Job description: The School of Mathematics is seeking applications for an Assistant Professor in High-performance Computing. The successful candidate will have demonstrated exceptional research promise in Computational Mathematics/Numerical Analysis with experience in High-performance Computing applications. With the opening of this position, we seek to expand our existing research strengths in this direction. The School of Mathematics, which at Trinity includes Theoretical Physics, boasts research groups in Applied and Numerical Linear Algebra (ANLA) as well as a computationally- focused high-energy physics group working in Lattice QCD. The School seeks to augment its existing strengths in both Mathematics and Theoretical Physics by further building computational and high-performance computing expertise while complementing the work of our Lattice and ANLA groups. The post combines research and teaching; the appointee will contribute to undergraduate and postgraduate education and supervision, including to students on the School's taught MSc degree in High Performance Computing, with particular interests in candidates who are able to offer/develop lectures complementary to those in our existing M.Sc. in HPC. Candidates working in any area within Computational Mathematics/Numerical Analysis will be considered, with preference for those with experience in High-Performance Computing applications. In particular, candidates working in areas concerning large-scale computations in optimisation and stochastic partial-differential equations are encouraged to apply. ------------------------------------------------------- From: Charley Denton cdenton@aimsciences.org Date: May 14, 2026 Subject: Contents, AIMS New Article: ACSE Vol. 8, Art. 3 Advances in Computational Science and Engineering Volume: 8, Art. 3 June 2026 https://www.aimsciences.org/ACSE/article/2026/8/0 Physics informed neural network framework for modified kawahara equations Santosh Anand, Srinivasan Natesan and Şuayip Toprakseven ------------------------------------------------------- From: Charley Denton cdenton@aimsciences.org Date: May 14, 2026 Subject: Contents, AIMS New Articles: CAC Vol. 9, Art. 1, 3 Communications on Analysis and Computation Volume: 9, Art. 1, 3 September 2026 https://www.aimsciences.org/CAC/article/2026/9/0 Sigmoid mass function generation for multi-ordinal classification model fusion Shuhui Bi, Yang Cao, Tao Shen, Kang Zhao and Liyao Ma Fast implementation of nonlinear fractional diffusion equations with time delay on unbounded spatial domain Jing Li, Fengping Mao and Zhenrong Chen ------------------------------------------------------- From: Charley Denton cdenton@aimsciences.org Date: May 14, 2026 Subject: Contents, AIMS New Article: FAM Vol. 1, Art. 4 Frontiers in Applied Mathematics Volume: 1, Art. 4 June 2026 https://www.aimsciences.org/FAM/article/2026/1/0 Quantitative photoacoustic imaging in three-dimensional elastic media Tian Ding and Yan Ma ------------------------------------------------------- From: Charley Denton cdenton@aimsciences.org Date: May 14, 2026 Subject: Contents, AIMS New Article: MFC Vol. 13, Art. 1 Mathematical Foundations of Computing Volume: 13, Art. 1 October 2026 https://www.aimsciences.org/mfc/article/2026/13/0 Approximation via Erdélyi-Kober type Szász-Kantorovich operator Pinakadhar Baliarsingh and Subhasmita Maharana ------------------------------------------------------- rom: Tristan van Leeuwen t.van.leeuwen@cwi.nl Date: May 11, 2026 Subject: Call for papers, Springer Künstliche Intelligenz special issue AI4Science We are happy to announce a special issue on Scientific Machine Learning for the Künstliche Intelligenz journal (Springer). Its aim is to showcase recent methodological developments, theoretical insights, and application driven advances at the interface of numerical analysis, scientific computing, and machine learning. Tentative timeline - Submission deadline: July 15, 2026 - First review round: October 15, 2026 - Final acceptance: December 15, 2026 More details can be found here: https://link.springer.com/collections/ibcajgbjgj With best regards, Victorita Dolean (Eindhoven U. of Technology, the Netherlands) Alexander Heinlein (Delft U. of Technology, the Netherlands) Alena Kopanicakova (University of Toulouse, France) Tristan van Leeuwen (Centrum Wiskunde & Informatica and Utrecht U., the Netherlands) ------------------------------------------------------- From: Marc Van Barel marc.vanbarel@cs.kuleuven.be Date: May 13, 2026 Subject: Call for papers: Special Issue of the Journal Numerical Algorithms on the occasion of the 65th anniversary of Nicola Mastronardi Nicola Mastronardi is a prolific researcher in numerical linear algebra, with a focus on matrix computations, algorithms for structured rank matrices (like semiseparable and Toeplitz matrices), eigenvalue problems, and scientific computing applications. He has co-authored numerous highly-cited scientific papers and collaborated with researchers from various international institutions. His work involves developing efficient algorithms for complex mathematical problems in fields such as medical diagnostics (e.g., magnetic resonance spectroscopy). Topics of this special issue are, but not limited to, Numerical Linear Algebra, Numerical Analysis, Systems and Control Theory, Scientific Computing, Orthogonal Polynomials. Submissions should be following the guidelines of the Journal Numerical Algorithms and can be send in till the end of January 2027 using the submission system of the journal. The corresponding collection is called "NM65". ------------------------------------------------------- End of Digest *************************