Mathematical Biology 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.

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.

Genomics, proteomics and imaging now measure molecules and cells across many scales. This workshop examines how mechanistic models can integrate those measurements and biological dynamics to explain and engineer cellular behaviour. Researchers in single-cell analysis, dynamic proteomics, quantitative imaging, synthetic biology and theory will connect experimental and computational approaches. The programme links three themes: cell dynamics and interactions; molecular mechanisms and engineering; and rigorous quantitative models. Sessions address multiscale modelling, molecules over time, large-scale perturbations, prediction of cell states, dynamic processes, and stem-cell engineering. Virtual participation includes livestreamed talks, questions and discussion, plus available recordings for four weeks; individual speakers may decline recording. Virtual participants cannot submit presentation abstracts. Fees: PhD students €175, academia €200, industry €275; card payment is required. Virtual registration closes 10 November 2026. On-site registration is closed. Programme times are Europe/Berlin (CET, UTC+1): 17 November opening at 13:15 and talks from 13:30; 18 and 19 November sessions from 09:00; 20 November from 10:00, with closing remarks at 13:15–13:30.

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.

Mechanistic cancer models and data-driven learning offer complementary ways to understand tumour behaviour and improve individualized treatment. This workshop explores how mathematical modelling can be combined with machine and deep learning, bringing together data scientists and mathematical oncologists. Plenary lectures survey current developments, while collaborative group projects develop algorithms that integrate mechanistic knowledge with observations. The programme aims to turn methodological exchange into sustained collaborations and more informative approaches to personalized cancer care.

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.

This school and workshop joins physics, applied mathematics and ecology to understand ecological dynamics and biodiversity across scales. Students learn to connect empirical data with individual-based models, differential equations, stochastic dynamics and complex interaction networks. The curriculum addresses marine species fluctuations, metapopulations, microbial ecology, animal movement, spatial scaling of plant communities, habitat fragmentation and evolutionary rescue. The January 23–24 workshop includes invited and contributed talks, posters, and discussion of theoretical ecology's future in South America. Master's and doctoral students are the principal school audience; advanced undergraduates and postdoctoral researchers may also apply. There is no registration fee, and limited travel and local support is available. School applications closed on 25 October 2026; the workshop application deadline is 20 November 2026.

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.

Machine learning has enabled advances in protein design and genetic circuits, but biological engineering still faces problems of interpretability, uncertainty and connections between molecular and system-level behaviour. Applied mathematicians, learning researchers and synthetic biologists will explore statistical methods for complex biological data, models that expose mechanisms, stochastic descriptions of noisy systems, multiscale modelling from molecules to populations and robust optimization for design under uncertainty. The workshop aims to develop mathematical foundations for more dependable biotechnology.

Biological mechanisms often have to be reconstructed from indirect measurements such as microscopy images, gene activity and cellular time series. This workshop examines inverse problems in living systems, where noise, complexity and diversity challenge existing mathematical approaches. Mathematicians, physicists, computer scientists and biologists will explore methods including deep learning and models informed by physical constraints to infer hidden cellular, genetic and neural mechanisms from experimental data.