Topic: digital twins

Raymundo Arróyave discusses alloy discovery guided by both metallurgical knowledge and Bayesian optimization. The approach combines physical models, high-throughput CALPHAD calculations, microstructural information and experimental feedback to search chemical and processing spaces that are difficult to explore through data alone. Examples involving high-entropy and refractory alloys address multiple objectives and constraints, including feasibility, correlated properties, uncertainty and microstructural sensitivity. The seminar then connects these decision methods to the Autonomous Robotic Me

Explore how evidence can support decisions across livestock production, nutrition, rural economies and land management. The programme connects multi-criteria assessment, life-cycle analysis, system-level modelling, carbon footprints and digital twins, considering environmental, nutritional, economic and social outcomes together. Sessions examine assessment beyond farm boundaries, scenario modelling, harmonization of on-farm tools, and the translation of complex evidence into practical decisions. Discussion panels address uncertainty, trade-offs, model fitness and implementation. The meeting br

Develop methods to detect, quantify and visualize errors and biases in heterogeneous geographic data for digital twins. Research combines interactive visualization, AI-assisted analysis and empirical evaluation, including crowd-sourced observations and remote-sensing data. The EDT-funded doctorate is hosted by the AVIZ team and supervised by Maria Lobo-Gunther. English-language applications only. Appointment: 3 years; advertised start 2027-10-01. Monthly gross salary : 2.300 euros.

Develop and evaluate AI-enabled connected vehicles and smart mobility systems. Research combines transportation data, digital twins, cooperative driving, infrastructure control, vehicle-in-the-loop testing and real-world demonstrations to improve energy efficiency and transport performance. 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.

Develop AI and data-science methods for manufacturing quality, monitoring and process optimisation in the Manufacturing Systems Analytics group. Work combines multimodal sensor streams, process data and digital twins, with opportunities to deploy models at the edge and on distributed systems. The Manufacturing Demonstration Facility provides experimental and computational resources. Appointments last up to 24 months, with extensions dependent on performance and funding.

Integrate and demonstrate human–robot collaboration technologies in industrial and new civilian settings. Scope includes safety, task allocation, ergonomics, extended reality, localisation and digital twins. Topic 2.1 funds projects up to €250,000; Topic 2.2 up to €170,000. Projects run for ten months from January 2027, with three milestone-linked payments. Submit the mandatory proposal and budget through F6S by 4 November 2026 at 17:00 Brussels time. Apply as a consortium with at least one SME; universities and research organisations may hold no more than 30% of the budget. UK and Swiss entit

Luca Pellegrino and Gabriele Intermite discuss a light-responsive synthetic skin inspired by cephalopod camouflage and specialised polymers used in protective clothing. Leonardo Maccari interviews Ion Turcanu about digital twins for autonomous and remote driving, connecting materials research with an applied technology discussion.

Over the past decade our community has made substantial progress in the construction of anatomically detailed network models of the cortical tissue. Thanks to advances in computer hardware and simulation technology, researchers can now routinely work with these models at the natural density of neurons and synapses. Moreover, the availability of cloud services means that such investigations can be carried out without having to install either the model or the simulation software. A recent workshop analyzed the impact of a specific model of the cortical microcircuit, published ten years ago . The

Steven Niederer and Richard Wilkinson discuss personalised mathematical models of patients’ hearts and their potential use in care. The conversation connects digital twins and the CVDNet project with research on representing, calibrating and using uncertainty in predictions. It also traces how this work develops ideas from the earlier Fickle Heart research programme.

Over the past decade, neuroscience, cognitive science and computer science (“AI”) converged to create specific, image-computable, deep neural network models intended to appropriately abstract, emulate and explain the mechanisms of primate ventral visual processing, up to its deepest neural level, the inferior temporal cortex (IT). Because these leading neuroscientific emulation models — aka “digital twins” — are fully observable and machine-executable, they offer predictive and potential application power that our field’s prior conceptual models did not. Our team’s ongoing work is aimed at ask

As tiny robots become individually more sophisticated, and larger robots easier to mass produce, a breakdown of conventional disciplinary silos is enabling swarm engineering to be adopted across scales and applications, from nanomedicine to treat cancer, to cm-sized robots for large-scale environmental monitoring or intralogistics. This convergence of capabilities is facilitating the transfer of lessons learned from one scale to the other. Cm-sized robots that work in the 1000s may operate in a way similar to reaction-diffusion systems at the nanoscale, while sophisticated microrobots may have