Topic: simulation

Study molecular reaction chemistry in aqueous and organic media using simulation, statistical mechanics and machine learning. The Chemical Dynamics Group seeks scalable computational workflows, coordinated with spectroscopy experiments, to understand structure, thermodynamics and reaction dynamics. Applications are made on the employer’s recruitment portal; no closing date is stated. Initial appointment up to 24 months, with extensions dependent on performance and funding.

Statistical Sciences invites applications for a tenure-stream position starting July 1, 2027. Research should advance computational foundations of data science, including simulation, inference, optimization, randomized numerical methods or scalable high-dimensional algorithms. The role combines independent funded research with teaching and service. A relevant PhD and research and teaching excellence are required. Salary: CAD 140,000–190,000 annually. Submit a cover letter, CV, research statement, teaching dossier and three reference letters through AcademicJobsOnline by December 7, 2026. Appli

This feasibility-study competition supports collaborative projects that accelerate and commercialise battery technologies, respond to a specific sector and market demand, remove industry hurdles and strengthen the UK battery value chain. In-scope work includes materials extraction and processing, cell and pack technologies, manufacturing tools, quality control, diagnostics, testing, simulation and digital tools. Projects must request £70,000 to £500,000, last 6 to 18 months, start no earlier than 1 May 2027 and finish by 31 March 2031. The competition closes on 2 December 2026 at 11:00am UK ti

Justin Johnson joins Sam Charrington to discuss world models and spatial artificial intelligence. Topics include representations of three-dimensional environments, simulation and the role of such models in enabling systems to reason about and act within the physical world.

Graphics processing units (GPUs) are widely available and have been used with great success to accelerate scientific computing in the last decade. These advances, however, are often not available to researchers interested in simulating spiking neural networks, but lacking the technical knowledge to write the necessary low-level code. Writing low-level code is not necessary when using the popular Brian simulator, which provides a framework to generate efficient CPU code from high-level model definitions in Python. Here, we present Brian2CUDA, an open-source software that extends the Brian simul