Applied Mathematics workshops

This workshop connects mathematical and theoretical neuroscience approaches to the dynamics of densely connected recurrent spiking networks. Mean-field methods link individual-neuron dynamics with population behaviour, while low-dimensional collective dynamics and low-rank connectivity provide complementary descriptions informed by experiments and simulations. Researchers with mathematical and physics backgrounds alternate presentations to compare these perspectives. Public research lectures run from Monday afternoon through Wednesday, followed by doctoral tutorials on Thursday and Friday at the Bernoulli Center, EPFL, Lausanne. Registration begins at 13:30 on 2 November, with the introduction at 13:45 and talks from 14:00. Tuesday and Wednesday lectures and Thursday and Friday tutorials start at 09:00. Times are Europe/Zurich, CET (UTC+01:00). Seats are limited; researchers from outside EPFL pay CHF90 and commit to attending the lecture sessions. Tutorials are restricted to PhD students. Separate registration forms for doctoral students and other researchers are linked on the official workshop page. Preparation assumes mathematics or physics at master’s level and familiarity with computational neuroscience.

This RICAM workshop examines the numerical foundations of reliable deep-learning computation. Low-precision and mixed-precision arithmetic, quantization and parallel GPU computation enable larger models and deployment on constrained devices, while introducing questions about error, stability and performance. Researchers from theoretical and applied communities will compare methods for stable training and efficient inference and identify directions for further work. The programme brings together expertise in numerical analysis, machine learning and hardware-aware computation. The in-person workshop runs on 2–6 November at RICAM, Science Park 2, fourth floor, Altenberger Straße 69, Linz. Monday registration and welcome run 14:00–14:40, followed by talks until 17:00. Tuesday through Friday sessions begin at 09:00; Friday’s programme ends at 11:40. Times are Europe/Vienna, CET (UTC+01:00). Register through the special-semester form, select Workshop 2 and Regular Participant, and use an institutional email address to verify affiliation. Registration is binding; the organizer asks for cancellation at least one week before the workshop and states that unreported non-attendance can exclude participants from future events.

The second M4H workshop brings mathematics, data science and medical research together to improve care. Mathematical models, numerical methods, statistics and machine learning support precision medicine, healthcare-resource allocation and multimodal patient-data analysis. Keynotes examine evolutionary cancer treatment and model-driven digital twins, longitudinal health records, topology and geometry for cyclic gene expression, statistical approaches to individual mental-health variation and patient-specific blood-flow simulation. Panels connect these methods with cardiovascular medicine, health data science and sustainable brain health. The Department of Mathematics at Politecnico di Milano hosts the in-person workshop on 11–13 November 2026 in Aula Rogers, Building 11, Via Ampère 2, Milan. Posters use Aula Vetrata, Trifoglio Building 13, Via Bonardi 9. The programme runs 11 November 14:00–19:30, 12 November 09:00–18:10 and 13 November 09:00–16:00. Times are Europe/Rome, CET (UTC+01:00). Registration is free and open until 15 October through the form on the official workshop page. Speaking slots are invitation only; general attendance is open, and participants may submit poster abstracts.

Connect numerical approaches to classical and quantum initial-boundary-value problems. The workshop examines deterministic wave propagation, fluid dynamics and general relativity alongside fluctuating quantum fields and hydrodynamics. Invited perspectives and contributed talks explore shared modelling challenges, including symmetry-preserving and mimetic discretisation, summation-by-parts methods, action-based formulations, lattice field theory, stochastic partial differential equations and quantum computing. Researchers in theoretical physics and applied mathematics will compare methods and identify opportunities for collaboration across these neighbouring fields. 19 November 2026 at 09:00 through 21 November at 17:00, Asia/Seoul (KST, UTC+9). Participant registration closes on 8 November 2026 and requires an Indico account. Capacity is 70. Contributed abstracts are due 25 October.

Solve shape-analysis problems in R using measurements, landmarks and outlines. The programme develops data organisation and image processing before geometric transformations, alternative superimposition methods and Procrustes analysis. Participants visualise shape differences, test allometry and multivariate hypotheses, and compare principal-component, discriminant and regression approaches. Outline analysis introduces several Fourier representations and their statistical interpretation; participants can bring their own morphological datasets. Live sessions: 10, 11, 14, 15, 16, 17 and 18 December, 12:00–17:00, Europe/Madrid (CET, UTC+01:00). Total 40 hours: 35 live plus five independent. English-language live online course; Fee €495 until 31 October, then €565; Ambassador rates €396/€452. VAT included. Capacity: 16. Basic R, multivariate statistics and geometric morphometrics are recommended; this is not an introductory morphometrics course. Registration requires acceptance; payment follows confirmation. Recordings are provided, but live attendance is required for a certificate.

The second UK Theoretical Neuroscience Workshop is a one-day meeting of talks and posters on mathematical and computational approaches to brain function, organised by Stephen Coombes (University of Nottingham) and Dimitrios Pinotsis (City St George's, University of London). Talks include Peter Latham (UCL) on time and task management in complex environments; Magnus Richardson (University of Warwick) on spatiotemporal coarse-graining of activity within neurons and across networks; Rafal Bogacz (University of Oxford) on predictive dendrites as a foundation for biological learning; Arnd Roth (UCL) on brain-wide dendritic signals that exhibit circuit-specific behavioural modulation; Mark Humphries (University of Nottingham) on cortical control of rhythmic and discrete arm movements; Vladimir Litvak (UCL) on why the low effective dimensionality of the human functional connectome does not invalidate lesion network mapping; and Massimiliano Di Luca (University of Birmingham) on temporal inference in perception and coordinated action. Angus Chadwick (University of Edinburgh) and Eirini Mavritsaki (Birmingham City University) also speak. The workshop runs from 09:00 to 18:10 on Friday 18 December 2026 at City St George's, University of London, with talks in the Northampton Suite (B411) and posters in The Pavilion of the University Building, Northampton Square. Attendance is free but registration is mandatory. Poster abstracts are due on 20 November 2026, and a poster award will be given.

Quantify biological shape variation and its covariation with the physical environment through geometric morphometrics. This introductory workshop develops landmark and semilandmark configurations, data acquisition and digitisation, Generalized Procrustes Analysis and shape space. Participants compare alternative alignment methods, visualise thin-plate-spline deformations in two and three dimensions, and use principal components, multivariate regression and allometry to interpret variation. Practical work uses TPS software and MorphoJ, with emphasis on interpreting biological questions through geometric and statistical methods. 14, 15, 18, 19 and 20 January 2027, each 14:00–19:00, Europe/Madrid (CET, UTC+1); 25 live hours. English; intended for graduates and researchers in biological sciences and related disciplines. No previous morphometrics experience required; familiarity with multivariate statistics recommended. Eighteen places. EUR 476 through 31 October 2026, then EUR 580; Ambassador Institution fees EUR 380.80 and EUR 464, respectively. Live attendance is required for the certificate. Payment follows acceptance; advertised fees include VAT.

Learn to quantify and interpret biological form using two- and three-dimensional geometric morphometrics. Lectures and practical sessions cover landmark, semilandmark, outline and surface data, digitisation methods, study design and data-quality checks. Generalized Procrustes Analysis provides the foundation for principal components, group comparisons, linear models and allometry. Further sessions address symmetric structures and the possibilities and limitations of machine-assisted data acquisition. Participants assemble a basic analysis workflow and can discuss their own datasets. Teaching emphasises accessible graphical software, with R implementations introduced according to participants’ interests. 25–27 January 2027, daily 13:00–19:00 Europe/Berlin (CET, UTC+1). Live online, taught in English. Fee EUR 330 for this three-day course. Intended for researchers beginning geometric morphometrics or seeking a more structured foundation.

Workshop bringing together researchers working on AI for learning dynamics from data, with a special focus on information-theoretic methods. Topics include predictive information, the information bottleneck, latent-variable models, entropy and mutual-information estimation, world models of biological systems, and connections to dynamical systems and control theory. The workshop is part of the six-week NITMB program “Image-Based Scientific Machine Learning for Theories of Biological Dynamics Across Scales” (February 1–March 12, 2027). Program: AI in Biological Dynamics Scientific Focus — details for the six-week NITMB program: https://www.nitmb.org/ai-in-biological-dynamics-scientific-focus Application deadlines: November 9, 2026 for applicants requesting travel and lodging support; December 8, 2026 for local applicants. Students, postdocs and early-career researchers are encouraged to apply. See the Application tab on the workshop website.

Develop phylogenetic comparative methods from their probabilistic foundations using Julia. Participants implement likelihood and Bayesian inference, including Markov chain Monte Carlo, and study Brownian motion, continuous-time Markov chains and birth–death processes. These tools are applied to trait evolution, biogeography and diversification, including the effects of environmental and biotic interactions. The practical course is intended for researchers familiar with programming, probability and phylogenetics; prior Julia experience is not required. Sessions on 1, 3, 5, 8, 10 and 12 March 2027, 14:00–18:00 Madrid time (CET). Fee including VAT: EUR 492 through 31 December 2026, then EUR 576; Ambassador Institution rates EUR 393.60 and EUR 460.80. Limited to 18 participants. Acceptance is confirmed before payment. Delivered live online in English with practical exercises. Live attendance is required for a certificate.

Explore path-integration techniques linking quantum mechanics, quantum field theory and gravity. Five themes connect worldline methods, strong external backgrounds, heat-kernel expansions and resurgence, on-shell quantities, and geometry in first quantisation. Discussion includes curved spaces, superspace and nontrivial topology, as well as representations of wavefunctions, scattering amplitudes and gravitational waveforms. Review lectures introduce challenges in each area, followed by invited and contributed talks, two poster sessions and extended collaborative discussions across research communities. 22 March 2027 at 17:00 through 2 April at 13:30, Europe/Paris. The local timezone changes from CET to CEST on 28 March. Expressions of interest close on 15 December 2026 and participation is confirmed by the end of the year. An Indico account is required. Capacity is 70. Estimated fees, including accommodation and meals, are EUR 1,330 for established or senior scientists and EUR 940 for early-career researchers, payable on arrival; limited travel support is being sought.

Methods in Computational Neuroscience (MCN) is a four-week Marine Biological Laboratory course that introduces the computational and mathematical techniques used to address how the brain solves problems at levels of neural organisation ranging from single membrane channels to operations of the entire brain. In each of the first three weeks the course moves up a level of complexity, from molecular and cellular to network to cognitive and behavioural, asking whether biologically plausible mechanisms can explain how nervous systems solve specific computational problems, how such problems can be decomposed, and how those decompositions relate to observable properties of neurons and circuits and their molecular building blocks. Core presentations are given jointly by theorists and experimentalists who have worked on the same problems, with optional first-week tutorials on dynamical systems, information theory, dimensionality reduction, neural network modelling and simulation in Python and MATLAB. Laboratory exercises combine quantitative analysis of experimental data with analytic and numerical exploration of models, often in teams mixing theoretical and experimental backgrounds, and the fourth week is reserved for student projects with resident faculty. The 2027 course, directed by Stefano Fusi (Columbia University) and Roozbeh Kiani (New York University), runs from 24 July to 21 August 2027 and is limited to 24 graduate students, postdocs and faculty from fields ranging from zoology and neurobiology to physics, engineering and mathematics. Applications are due on 10 March 2027, and financial aid is offered.

The School on Analytical Connectionism is a two-week summer course on analytical tools, including methods from statistical physics and probability theory, for probing neural network models of higher-level cognition, bringing together neuroscience, psychology and machine-learning communities. The 2027 school, held in Boston from 2 to 13 August 2027, focuses on interpretability in reasoning and mathematical cognition: how children or artificial systems use and acquire mathematical concepts, how mathematical intuition and expertise develop and interact, and how studying the heuristics and abstractions that AI systems develop may deepen understanding of human mathematical cognition. The first week offers core lectures on mathematical methods for neural network analysis and on key connectionist models linked to experimental observations; the second week offers frontiers lectures. Participants also join tutorials, poster sessions and contributed talks, work in teams on research projects that they pitch in week one and present at the end, and co-author peer-reviewed lecture notes collected into a special issue. The school is directed by Erin Grant (University of Alberta & Amii) and Stefano Sarao Mannelli (Chalmers University of Technology & University of Gothenburg), with SueYeon Chung (Harvard University & Flatiron Institute) and Andrew Saxe (University College London) as advisors. Applications open on 1 February 2027 and close on 1 April 2027 (AoE); first-round outcomes are communicated on 17 May 2027.