From: Alex Townsend Date: Fri, 16 Oct 2026 08:26:56 -0400 Subject: NA Digest, V. 26, # 42 To: na-digest-l@lists.cornell.edu NA Digest Friday, October 16, 2026 Volume 26 : Issue 42 Today's Editor: Alex Townsend Cornell University townsend@cornell.edu Today's Topics: Tomography Training and Mini-Hackathon, Lund Sweden, Nov 2026 Biennial Numerical Analysis Conference 2027, Glasgow, Scotland Ph.D. Position in Financial Mathematics at BMU (Hero Group), India Postdoc position in Numerical Linear Algebra and HPC at LNCC-Brazil Postdoc positions in Computational Modeling at Morgan State University Tenure Track Position at East Texas A&M University Distinguished Professor, UNC-Chapel Hill Department of Mathematics Contents, AIMS New Volume: IPI Vol. 29 Contents, AIMS New Volume: MCRF Vol. 19 Call for Papers, EPJ ST/EPJ Plus: Fractional and Delayed Dynamics ICIAM 2027: Call for contributions - deadline 7 December 2026 Call for contributions: preCICE Workshop, Delft, Mar 2027 See this issue of NA Digest on the web at: https://na-digest.coecis.cornell.edu/na-digest-html/26/v26n42.html Submissions, FAQs, and archives: https://na-digest.coecis.cornell.edu/ ------------------------------------------------------- From: Jakob Sauer Jørgensen jakj@dtu.dk Date: October 11, 2026 Subject: Tomography Training and Mini-Hackathon, Lund Sweden, Nov 2026 A three-day training and mini-hackathon on tomographic imaging will take place November 10-12, 2026, at LINXS in Lund, Sweden. Participants will gain hands-on experience with three open-source libraries for tomography: gVXR for X-ray imaging simulation, the Core Imaging Library (CIL) for tomographic reconstruction, and qim3d for 3D image analysis, including segmentation and quantification. The programme combines introductory lectures and practical exercises with a mini-hackathon, offering opportunities to explore advanced topics and work on participants' own data or imaging problems with guidance from the software developers. Beginners and experienced researchers are welcome, including application scientists, facility staff, research software engineers, and computational imaging scientists. An informal Posters & Pizza session will be held on the first evening to encourage collaboration and knowledge sharing. Location: LINXS, The Loop, Rydbergs torg 4, Lund, Sweden. Details and registration: https://indico.linxs.lu.se/event/731/overview ------------------------------------------------------- From: Gabriel R. Barrenechea gabriel.barrenechea@strath.ac.uk Date: October 14, 2026 Subject: Biennial Numerical Analysis Conference 2027, Glasgow, Scotland It is our pleasure to announce the 31st Biennial Conference on Numerical Analysis. The meeting will take place during June 22-25, 2027 at the University of Strathclyde, Glasgow, Scotland. This long established conference is open to all researchers in the field, and you are invited to contribute a talk on your current work. PhD students and young researchers will find the environment particularly welcoming. The following distinguished researchers have accepted invitations for plenary lectures at the conference: * Julianne Chung, Emory University * Colin Cotter, Imperial College London * Lars Dienning, Bielefeld University * Mark Embree, Virginia Tech * Alexandre Ern, ENPC, Paris * Vanni Noferini, Aalto University * Malgorzata Peszynska, Oregon State University * David Silvester, University of Manchester * Aretha Teckentrup, University of Edinburgh * Philippe Toint, University of Namur The A R Mitchell lecture will be given by David Silvester, and the Fletcher-Powell lecture by Philip Toint. The call for minisymposia proposals is now open, with details on the submission process available at https://numericalconference.org/minisymposia.html Please note that the deadlines for submitting proposals and abstracts will be earlier than for previous editions of the conference: * Minisymposium proposal submission deadline: January 15, 2027 * Contributed talk submission deadline: February 28, 2027 Further information on registration, minisymposia proposals, etc., can be found at the Conference's web page https://numericalconference.org ------------------------------------------------------- From: Luckshay Batra luckshay.batra@bmu.edu.in Date: October 10, 2026 Subject: Ph.D. Position in Financial Mathematics at BMU (Hero Group), India Ph.D. Position in Applied Mathematics and Quantitative Finance BML Munjal University (BMU), Gurugram, Haryana, India, invites applications for its Winter 2026 Ph.D. programme. I have a Ph.D. position available in my research group in the School of Engineering and Technology. Suitable candidates should be interested in Applied Mathematics and Quantitative Finance. Research areas include entropy and information-theoretic methods in finance, uncertainty and risk modelling, option pricing, stochastic processes, and differential equation modelling. The university fellowship is INR 45,000 per month for the first two years and INR 55,000 per month for the next two years. An annual professional development grant is also available. Application deadline: 2 November 2026. Application: https://bit.ly/4rOVBla Programme details: https://www.bmu.edu.in/courses/ph-d/ Interested candidates may email their CV to luckshay.batra@bmu.edu.in. ------------------------------------------------------- From: Frédéric Valentin valentin@lncc.br Date: October 15, 2026 Subject: Postdoc position in Numerical Linear Algebra and HPC at LNCC-Brazil The Innovative Parallel numErical Solvers (IPES) research group at the Brazilian National Laboratory for Scientific Computing (LNCC) invites applications for a two-year postdoctoral research position within the GEOMECH project. The selected candidate will conduct research in numerical linear algebra, focusing on the development of efficient and scalable solvers for linear and nonlinear systems arising from multiscale flow and geomechanical simulations in fractured and vuggy carbonate reservoirs. Research topics include, but are not limited to: - Domain decomposition and multigrid methods. - Direct and iterative solvers, including advanced preconditioning techniques. - Hybrid parallel computing strategies (intra-node and inter-node parallelism). We seek applicants with: - A Ph.D. in Mathematics, Engineering, Computer Science, or a related field. - A strong theoretical background in numerical analysis and computational mathematics. - Demonstrated programming experience in numerical linear algebra and scientific computing. Please send the following documents to valentin@lncc.br: - Curriculum vitae (CV). - A one-page statement of research interests and motivation. - One letter of recommendation. Applications received before November 16, 2026, will receive full consideration. Research group: https://ipes.lncc.br/ ------------------------------------------------------- From: Pilhwa Lee pilhwa.lee@morgan.edu Date: October 15, 2026 Subject: Postdoc positions in Computational Modeling at Morgan State University Postdoctoral Fellow #1) Computational Neuronal Circuitry & Endocrine Modeling Institution: Morgan State University, Baltimore, MD, USA Project: Digital twins for the therapeutics of gestational diabetes (NIH- funded: OTA-26-004) Position Summary: We are seeking a highly motivated Postdoctoral Fellow to contribute to the computational modeling of hypothalamic neuronal excitability and metabolic adaptation as part of an NIH-funded digital twin project. This research focuses on the complex neuronal networks modulated by metabolic and placental hormones during pregnancy. The successful candidate will drive a crucial phase of our multi-aim workflow, constructing mechanistic models that capture how circulating hormones alter the excitability of feeding circuitry to regulate glucose control and energy balance across healthy, obese, and diabetic maternal cohorts. Required Qualifications * Ph.D. in Applied Mathematics, Mathematical Biology, Computational Neuroscience, or a closely related discipline. * Proven expertise in building mechanistic mathematical models of neuronal excitability (e.g., Hodgkin-Huxley or network conductance models). * Advanced proficiency in MATLAB/Python programming for computational model development. * Strong track record of independent research and peer-reviewed scientific publications. Preferred Qualifications * Background in neuroendocrinology, hypothalamic circuitry, or metabolic regulation (e.g., glucose homeostasis). * Experience aligning complex computational models with variable clinical datasets, such as blood titration data or hormone profiles. * Ability to work in a collaborative, multi-disciplinary team setting encompassing systems biology, genetics, and clinical data collection. Postdoctoral Fellow #2) Computational Systems Biology Institution: Morgan State University, Baltimore, MD, USA Project: Digital twins for the therapeutics of gestational diabetes (NIH- funded: OTA-26-004) Position Summary: We are seeking a Postdoctoral Fellow to lead the computational modeling of 1) metabolic systems and 2) fluid balance related to hypertension. As part of an innovative NIH-funded grant, this project focuses on constructing patient-specific digital twins to advance glycemic management and therapeutic strategies across diverse pregnant cohorts. Required Qualifications * Ph.D. in Applied Mathematics, Mathematical Biology, Systems Biology, or a related discipline. * Strong background in mechanistic mathematical modeling of biological, endocrine, or physiological systems. * Advanced proficiency in MATLAB/Python programming. * Demonstrated record of scientific publication and strong writing skills. Preferred Qualifications * Prior experience with metabolic signaling, glucose-insulin models, or gastrointestinal dynamics. * Familiarity with Python/PyTorch or cross-disciplinary clinical research environments. Postdoctoral Fellow #3) Computational and statistical analysis of spatial biology Institution: Morgan State University, Baltimore, MD, USA Position Overview We are seeking a highly motivated and innovative Postdoctoral Fellow to lead the computational and statistical analysis of high-dimensional multi-modal spatial data. The successful candidate will develop and apply advanced statistical models to integrate spatial transcriptomics, clinical neuroimaging, and multiplexed tissue imaging datasets. You will play a critical role in bridging the gap between macro-scale brain imaging and cellular-level spatial omics. Key Responsibilities * Data Analysis & Pipeline Development: Lead the statistical analysis of spatial transcriptomics data (e.g., 10x Visium, Xenium, or MERFISH) and highly multiplexed imaging data (e.g., CODEX). * Multi-Modal Brain Mapping: Process and analyze neuroimaging datasets (e.g., structural MRI, fMRI, or PET) and integrate these macro-scale clinical images with micro-scale spatial multi-omics to build multiscale models of brain tissue. * Algorithm & Method Development: Design and implement novel statistical and machine learning methods for spatial domain identification, image segmentation, and cross-modality data alignment. * Collaboration: Work closely with experimentalists and radiologists to guide experimental design, ensure data quality, and iterate on analytical approaches. * Scientific Communication: Prepare high-impact manuscripts, present findings at national/international conferences, and assist in drafting computational sections for grant proposals. Required Qualifications * Education: Ph.D. in Applied Mathematics, Mathematical Biology, Biostatistics, Bioinformatics, Neuroinformatics, Data Science, or a related quantitative field. * Statistical Expertise: Strong foundation in statistical modeling, hypothesis testing, and spatial statistics. * Domain Experience: Proven hands-on experience analyzing spatial transcriptomics datasets, quantitative imaging sciences, and/or neuroimaging data. * Programming Skills: High proficiency in R and/or Python. Experience with relevant computational libraries (e.g., Seurat, Squidpy, SpatialExperiment). * Version Control & Compute: Experience with Git/GitHub and working in high-performance computing (HPC) or cloud environments. * Communication: Excellent written and oral communication skills, with a track record of peer-reviewed publications. Preferred Qualifications (Optional) * Proficiency with standard neuroimaging analysis software and pipelines (e.g., FSL, FreeSurfer, AFNI, SPM, or ANTs). * Experience with deep learning and computer vision techniques applied to biological or medical images (e.g., medical image registration, cell segmentation). * Strong background in neuroanatomy, neurobiology, or cognitive neuroscience. Contact Send me your CV to Pilhwa Lee, Pilhwa.lee@morgan.edu ------------------------------------------------------- From: Ricardo V Teixeira Ricardo.Teixeira@etamu.edu Date: October 14, 2026 Subject: Tenure Track Position at East Texas A&M University Assistant Professor of Mathematics (Tenure-Track) - Statistics and Data Science The Department of Mathematics at East Texas A&M University invites applications for a tenure-track Assistant Professor position beginning in Fall 2027. We seek a candidate with expertise in Statistics, Data Science, Machine Learning, or a closely related area. Candidates whose research connects mathematics and statistics with interdisciplinary applications, such as mathematical biology, biostatistics, artificial intelligence, computational science, or related fields, are especially encouraged to apply. The successful candidate will be expected to teach undergraduate and graduate courses, maintain an active research agenda, mentor students, and contribute to the service mission of the department, college, university, and profession. The department is particularly interested in candidates who can support and further develop programs in Statistics and Data Science. DUTIES & RESPONSIBILITIES • Teach undergraduate and graduate courses in Mathematics, Statistics, and Data Science in face-to-face, hybrid, and online formats. • Contribute to the development and expansion of courses and curricula in Statistics, Data Science, Machine Learning, and related areas. • Maintain an active scholarly research program that leads to publications in peer-reviewed scholarly publications, professional presentations, and pursuit of external funding opportunities. • Engage undergraduate and graduate students in research and mentorship. • Advise and mentor students in academic and professional development. • Provide service to the Department, College, University, community, and profession. • Maintain effective, professional, and collegial relationships with faculty, students, staff, alumni, and external partners. • Maintain on-campus office hours and participate in departmental activities. • Serve on departmental, college, and university committees as assigned. MINIMUM REQUIREMENTS Education: An earned Ph.D. in Mathematics, Statistics, Data Science, Applied Mathematics, or a closely related field (degree must be completed prior to the start date). Experience / Knowledge / Skills: • Evidence of potential for excellence in university-level teaching. • Demonstrated potential to establish and sustain a productive research program. PREFERRED QUALIFICATIONS • Research expertise in Statistics, Data Science, Machine Learning, Artificial Intelligence, Computational Mathematics, or related disciplines. • Experience teaching Statistics, Data Science, Machine Learning, or related courses at the undergraduate and/or graduate level. • Evidence of interdisciplinary collaboration. • Demonstrated record of scholarly publications and professional presentations. • Success in obtaining, or strong potential to obtain, external research funding. Commitment to student success, mentoring, and academic excellence. APPLICATION MATERIALS Please submit the following at our Employment website, https://www.etamu.edu/human-resources/employment/ • Cover Letter • Curriculum Vitae • Statement of Teaching Philosophy • Statement of Research Interests • Three professional references with complete contact information (unsolicited letters of recommendation will not be considered) • Transcripts (unofficial transcripts will be accepted with the application; official transcripts are required upon verbal offer) ADDITIONAL INFORMATION The college cannot support visa sponsorship for this position. The Texas A&M University System is an Equal Opportunity/Veterans/Disability Employer. About East Texas A&M University East Texas A&M University is a comprehensive public institution and a member of The Texas A&M University System. Located in Commerce, Texas, approximately one hour northeast of the Dallas-Fort Worth metroplex, the university serves a diverse student population and is committed to academic excellence, student success, and regional engagement. About the College of Science and Engineering The College of Science and Engineering (CoSE) provides innovative and student-centered education across the STEM disciplines. The college is dedicated to advancing scientific discovery, technological innovation, and workforce development through excellence in teaching, research, and service. CoSE promotes interdisciplinary collaboration and offers opportunities for faculty to engage students in research and creative activities that address real-world challenges. The college includes the departments of Biological and Environmental Sciences, Chemistry, Computer Science and Information Systems, Engineering and Technology, Mathematics, and Physics and Astronomy. About the Department of Mathematics The Department of Mathematics is a vibrant and collegial department committed to excellence in teaching, research, and service. The department offers undergraduate and graduate degrees in Mathematics, including programs with emphases in Data Science and Mathematics Education. Faculty members are engaged in a wide range of research areas, including probability and statistics, combinatorics, algebra, analysis, differential equations, coding theory, image analysis, and mathematics education. The department places a strong emphasis on student mentoring, interdisciplinary collaboration, and preparing graduates for careers in industry, government, education, and advanced study. The successful candidate will have opportunities to contribute to the continued growth of the department's Statistics and Data Science programs and to collaborate with faculty across the university. ------------------------------------------------------- From: Jingfang Huang huang@email.unc.edu Date: October 13, 2026 Subject: Distinguished Professor, UNC-Chapel Hill Department of Mathematics The UNC-Chapel Hill Department of Mathematics invites applications for a tenured Distinguished Professor. The position will also carry a secondary appointment as department chair. The successful candidate will provide visionary academic and administrative leadership for the Department of Mathematics, helping to shape and advance its intellectual direction and strategic priorities. In the chair role, the candidate will work collaboratively with faculty, staff, and university leadership to strengthen the Department’s excellence in teaching, research, and service. Responsibilities will include leading and overseeing the Department, teaching at the undergraduate and graduate levels, supervising graduate students, participating in academic service, and maintaining a strong, independent research program. Minimum Education and Experience Requirements: PhD in Mathematics, or related field. The candidate must have scholarly achievement appropriate for a tenured appointment at the level of full professor. Preferred Qualifications, Competencies, and Experience: Academic experience appropriate for appointment at the level of full professor, evidence of distinguished scholarship and excellence in teaching, and demonstrated leadership experience. Apply here: https://unc.peopleadmin.com/postings/326516 Applications received by November 16, 2026 will receive full consideration. Review of applications will continue on a rolling basis until the position is filled. At the time of application, candidates will be required to identify the names, titles, and email addresses of four professional references. Recommenders identified by the applicant will be contacted via the application portal with instructions for uploading their letters of support for finalists only. Proposed appointment would begin on 1/1/2028, but an earlier start date is negotiable. For further information on the Department, please visit our website at https://www.math.unc.edu The University of North Carolina at Chapel Hill is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, race, national origin, religion, sex, sexual orientation, or status as a protected veteran. ------------------------------------------------------- From: Charley Denton cdenton@aimsciences.org Date: October 15, 2026 Subject: Contents, AIMS New Volume: IPI Vol. 29 Inverse Problems and Imaging Volume: 29 April 2027 https://www.aimsciences.org/ipi/article/2027/29/0 A weighted nonlinear diffusion equation-based model for multi-feature image denoising Chen Wang, Zhichang Guo, Wenjuan Yao and Yi Ran A primal-dual splitting algorithm for monotone inclusions with applications Changchi Huang, Jigen Peng, Liqian Qin and Yuchao Tang Stable determination of coefficients in nonlinear dynamical schrödinger equations by carleman estimates Pranav Arrepu and Hanming Zhou A simple range characterization for spherical mean transform in odd dimensions and its applications Divyansh Agrawal, Gaik Ambartsoumian, Venkateswaran P. Krishnan and Nisha Singhal Learned alternating descent algorithm with extrapolation for dual-domain CT reconstruction Weina Wang, Yaosheng Chen, Yong Yang and Yunmei Chen Read more articles here: https://www.aimsciences.org/ipi/article/2027/29/0 ------------------------------------------------------- From: Charley Denton cdenton@aimsciences.org Date: October 15, 2026 Subject: Contents, AIMS New Volume: MCRF Vol. 19 Mathematical Control and Related Fields Volume: 19 December 2026 https://www.aimsciences.org/mcrf/article/2026/19/0 Preface Minh-Binh Tran and Emmanuel Trélat Uncertainty principles for a kinetic equation Nicola De Nitti and Minh-Binh Tran Strong convergence of truncated implicit Euler-Maruyama algorithms for the Wonham filters Xiaohang Ma, Xuerong Mao, Le Yi Wang and George Yin Weak convergence of utility-risk portfolios Kwok Chuen Wong, Sheung Chi Phillip Yam, Hailiang Yang and Harry Zheng Adaptative design for statistical estimation with ergodic controls for Ornstein-Uhlenbeck processes Alexandre Brouste, Youssef Esstafa and Alexandre Popier A "trembling hand perfect" equilibrium for a certain class of mean field games P. Jameson Graber Finite hybrid- and semi-Markov chains Jose Luis Menaldi and Maurice Robin Read more articles here: https://www.aimsciences.org/mcrf/article/2026/19/0 ------------------------------------------------------- From: Mattia Coccolo mattiatommaso.coccolo@urjc.es Date: October 09, 2026 Subject: Call for Papers, EPJ ST/EPJ Plus: Fractional and Delayed Dynamics Call for Papers: Joint EPJ ST / EPJ Plus Topical Collection "Fractional Calculus and Time-Delayed Dynamics" We invite submissions to a joint topical collection of The European Physical Journal Special Topics (EPJ ST) and The European Physical Journal Plus (EPJ Plus). The collection aims to bridge fractional calculus and time-delayed dynamics as complementary frameworks for modelling memory effects in dynamical systems. Topics of interest include: - Fractional operators and time delays as memory mechanisms - Stability, bifurcations, and dynamical behaviour - Numerical methods for fractional and delayed systems - Synchronization and control of systems with memory - Hybrid fractional-delay models and their applications - Applications in physics, engineering, and other fields Original research papers and review articles are welcome. Submission deadline: December 31, 2026 Publication year: 2027 EPJ ST offers Open Access publication. EPJ Plus provides a hybrid option, including subscription-based publication without APCs for authors without Open Access funding. EPJ ST: https://submission.nature.com/new-submission/11734/3 EPJ Plus: https://www.editorialmanager.com/epjp/default.aspx Guest Editors: M. T. Coccolo and M. A. F. Sanjuán Universidad Rey Juan Carlos, Madrid, Spain ------------------------------------------------------- From: Victorita Dolean-Maini v.dolean.maini@tue.nl Date: October 16, 2026 Subject: ICIAM 2027: Call for contributions - deadline 7 December 2026 Dear colleagues, The International Congress on Industrial and Applied Mathematics (ICIAM 2027) will take place on 12–16 July 2027 in The Hague, the Netherlands, under the theme “Mathematics for a Sustainable Future”. We invite minisymposium proposals and poster abstracts by 7 December 2026, which is also the deadline for grant applications. Submit a contribution: https://iciam2027.org/call-for-abstracts/ Registration is open, with early-bird rates available until 9 February 2027: https://iciam2027.org/registration/ The programme will also feature an Industry Day, connecting researchers and industry professionals through mathematical challenges and applications: https://iciam2027.org/program/industry-day/ Please share this announcement with interested colleagues. We look forward to welcoming you to The Hague! On behalf of the ICIAM 2027 Local Organising Committee ------------------------------------------------------- From: Benjamin Uekermann benjamin.uekermann@ipvs.uni-stuttgart.de Date: October 14, 2026 Subject: Call for contributions: preCICE Workshop, Delft, Mar 2027 preCICE is an open-source coupling library for partitioned multi-physics and multi-scale simulations. It enables the efficient, robust, and parallel coupling of separate single-physics solvers. preCICE treats these solvers as black boxes and, thus, only minimally invasive changes are necessary to prepare a solver for coupling. Ready-to-use adapters for well known open-source solvers are available: some examples of coupled codes include G+Smo, MercuryDPM, Nutils, OpenFOAM, deal.II, FEniCS, CalculiX, and SU2. The software offers methods for equation coupling, fully parallel communication, data mapping, and time interpolation. The 7th preCICE Workshop will be held for the first time outside Germany, at the Delft University of Technology in the Netherlands, on March 1-5, 2027, co-organized by Matthias Möller and his team within the Numerical Analysis group and the G+Smo community. The workshop is a coming together of the preCICE community to share ideas, experiences, and knowledge about using preCICE, and to learn from others in the process. Like always, we plan to have user and developer talks, hands-on training sessions, discussions with the developers about your applications and use cases, and plenty of opportunities for networking. We are looking for talks and posters that could be beneficial for the wider preCICE community. Are you developing a new adapter? Are you using preCICE for an exciting new application? Are you developing new methods that should not be missing from preCICE? If the answer to any of these questions was yes, we encourage you to submit a brief abstract for a 20-minute talk. Are you revisiting one of the classical preCICE use cases? Did you already present your work in a previous workshop? Then we would be very happy to catch up with your work, and we encourage you to present a poster. After review, and depending on the available slots, we might suggest a different presentation format than you originally applied for. Submission deadline: November 8. https://precice.org/precice-workshop-2027.html ------------------------------------------------------- End of Digest **************************