Applied Mathematics

A Nature Podcast episode examines a compact orbital detector designed to identify hidden nuclear devices and research on threats to Indigenous plant knowledge.

Lauren Williams introduces the positive Grassmannian and the surprising connections it creates across mathematics and physics. She explains links to waves, traffic and particle scattering, and discusses how research-level mathematical problems can help assess what artificial intelligence is capable of proving.

Optimal transport is a mathematical method to define a distance between probability distributions. This is particularly useful in various domains, including physics, biology, machine learning, and economics, among others. After introducing the Optimal Transport (OT) problem at finite temperature, we show how it can be formulated as a statistical physics problem. This approach allows us to derive very efficient algorithms to effectively compute the distance between two probability distributions. The a priori unrelated Schrödinger bridge (SB) problem is presented, and it is shown to be a dynamical version of the optimal transport problem. Indeed, the Schrodinger bridge looks for the most probable path in probability distribution space, which connects two given probabilities. The Schrodinger bridge problem, originally devised for freely diffusing particles, can be generalized to the case of interacting particles. It can be formulated in terms of functional integrals over bosonic fields, which allows us to derive partial differential equations that characterize the most probable paths in probability space. CARL VAN VREESWIJK MEMORIAL LECTURE 2026. Presented in the van Vreeswijk Theoretical Neuroscience Seminar series (formerly WWTNS) on 2026-04-15. Recording duration: 00:55:05.

Eirik Valseth discusses mathematical models of weather and storm surges and the computations used to make forecasts. Conversation in Norwegian.

Three two-year postdoctoral positions investigate the origins of irreversible behaviour through mathematical physics, theoretical physics and the history of physics. Topics include entropy, randomness, statistical mechanics, gravitational and holographic systems, and the historical development of chaos. Researchers join the Radboud Center for Natural Philosophy and collaborate across disciplines. The full-time gross monthly salary is EUR 3,706–5,760, according to experience. Apply by 14 October 2026 with a motivation letter, CV/publications, three referees and the position or positions sought. The preferred start is 1 January 2027, with an agreed later start possible up to 1 September 2027.

The University of Maryland Department of Mathematics invites applications for Brin/Novikov postdoctoral fellowships in mathematics and statistics, beginning in August 2027 or later. Appointments are initially for two years, with a possible third year, and combine research with teaching. The advertised application date is October 21, 2026; the description identifies this as the date for best consideration.

ETH AI Center offers approximately 8–12 postdoctoral fellowships for interdisciplinary AI research, with equal supervision by two principal investigators from different fields. Fellows develop their own projects spanning AI foundations and applications, join research exchanges and events, and may explore industry or entrepreneurial tracks. The appointment normally lasts two years, usually beginning in September 2027. Published salaries are CHF 92,500 in year one and CHF 97,200 in year two. A relevant doctorate must be completed at least three months before starting, and by June 2027 at the latest. Submit an online application by 27 October 2026 at 16:00 CET, following the programme guidelines and arranging reference letters.

ETH AI Center is recruiting approximately 8–12 doctoral fellows to propose and pursue interdisciplinary AI research, with two supervisors from different fields. Projects can address AI foundations or connect them with application areas. Fellows are based at the centre in Zurich and can pursue optional industry or entrepreneurship experience. Employment normally lasts three years, with a possible fourth year subject to progress; the usual start is September 2027. Published annual salaries are CHF 73,100, CHF 78,300 and CHF 83,500 in the first three years. Applicants need a relevant master’s degree completed at least three months before starting, and by June 2027 at the latest. Apply through the linked recruitment portal by 27 October 2026 at 16:00 CET. Reference letters must be arranged by the applicant.

The Society for Industrial and Applied Mathematics brings together applied mathematicians, probabilists, statisticians, computer and data scientists, economists and industry practitioners to examine mathematical and computational methods in quantitative finance. Themes include algorithmic trading, agentic and generative AI, climate finance, digital assets, credit and cyber risk, financial data science, insurance mathematics, market microstructure, stochastic control, systemic risk and volatility modelling. Minisymposium proposals are due 17 November 2026, followed by contributed lecture, poster and minisymposium-presentation abstracts on 15 December 2026.

The Society for Industrial and Applied Mathematics convenes its triennial conference on applied and numerical linear algebra. The programme covers matrix computations, machine learning, quantum simulation, inverse problems, high-performance computing, dynamical systems, model reduction, optimal transport, network science, tensor methods and related applications. Proposal submissions are currently open, with minitutorial and minisymposium proposals due 26 October 2026 and contributed presentation abstracts due 23 November 2026.

The Society for Industrial and Applied Mathematics convenes researchers developing and applying dynamical-systems methods across biology, chemistry, physics, climate science, social science, industry and data science. Themes include computational, experimental, theoretical and data-driven methods; AI-informed systems; fluid and climate dynamics; materials; networks; pattern formation; population dynamics; stochastic systems and tipping points. Minisymposium proposals are due 26 October 2026, followed by contributed lecture, poster and minisymposium-presentation abstracts on 23 November 2026.

Researchers and practitioners will discuss mathematical foundations of data science, including high-dimensional geometry, dimensionality reduction, scalable algorithms, uncertainty and machine learning. The conference takes place in person at the Salt Palace Convention Center on 16–20 November 2026. Registration is open, with early rates through 19 October; abstract and travel-support deadlines have passed. Registration also covers the co-located SIAM Imaging Science and Data Mining conferences.