The ANIMMA conference will feature a full-day workshop session on Monday, June 14, 2027, at the Clarion Congress Hotel Prague. The workshops will cover key topics ranging from fundamental research to practical applications, highlighting state-of-the-art research and developments across different fields.

For this edition, the topics will include:

• Instrumentation and measurement for nuclear research reactors;
• AI and advanced statistical approaches for nuclear measurements;
• Neutron spectroscopy.

The different workshop topics will be scheduled in parallel, allowing participants to switch between sessions throughout the day. Each workshop will feature seven invited talks, running from 10:15 am to 5:30 pm. A welcome coffee will be served from 9:45 am to 10:15 am.

In addition to the presentations, dedicated time will be allocated for discussions and exchanges between speakers and participants. These sessions will provide an opportunity to share ideas, bring together complementary skills and expertise, and identify potential avenues for collaborative research to address scientific and technological challenges.

The workshop registration fee will include the welcome coffee, lunch, and second coffee break.

For further information, please contact the Workshop Organization Chair:

Christelle REYNARD-CARETTE (christelle.carette@univ-amu.fr)

Conveners: Christelle Reynard-Carette (Aix-Marseille Université, France, christelle.carette@univ-amu.fr) and Gordon Kohse (MIT, USA, kohse@mit.edu)

Abstract: The development of nuclear instrumentation and measurement methods for major nuclear facilities, whether they are in the design, construction, or operational phases, is essential for conducting high-level scientific experiments, validating predictive models and proposing innovative solutions while meeting safety requirements. Such facilities will deliver extreme conditions requiring accurate, reliable and hardened sensors and detectors. The workshop will focus on different nuclear facilities thanks to seven invited presentations. The aim of the workshop will be to cover challenges, instrumentation, technologies, irradiation devices, safety systems and regulations. These topics will be addressed at various stages, depending on the types of reactors and their current status. The workshop will start with the Jules Horowitz Reactor led by CEA currently under construction in France and the VERONICA reactor project led by JSI in Slovenia. Then the workshop will deal with research reactors in operation in Europe (MARIA reactor by NCBJ in Poland, LVR-15 and LR-0 reactors by Research Centre Řež in Czech Republic) as well as the MIT reactor in the United States. One talk will focus on irradiation campaigns realized in 3 research reactors and the lessons learned from them for qualifying new sensor prototypes. Finally SOLO Micro-Modular Reactor will be presented by TERRA INNOVATUM. This workshop will provide scientists and experts with an opportunity to exchange views and identify potential future collaborations.

Conveners: Bertrand Pérot (CEA, France, bertrand.perot@cea.fr) and Malcolm Joyce (University of Lancaster, UK, m.joyce@lancaster.ac.uk)

Abstract: Artificial intelligence (AI) and advanced statistical methods—such as Bayesian approaches—combined with today’s powerful numerical computing capabilities, are driving major advancements in all fields of science, particularly in nuclear instrumentation and measurement. For example, AI enables more effective analysis of data from detectors, which is often voluminous, noisy, rare or incomplete (limit of detection). Machine learning algorithms can identify spectrometric or temporal signatures that are difficult to distinguish using conventional methods. AI can thus improve the detection, identification, and quantification of radionuclides. AI also facilitates real-time analysis and enables the automation of certain instrument calibration, control, and diagnostic operations. In nuclear facilities, these tools can improve process monitoring and the characterization of radioactive waste. In particular, AI makes it possible to fuse data from multiple sensors to obtain a more comprehensive characterization—with reduced uncertainties—of the environment or the radiological objects being measured. However, its use requires representative data—often obtained through numerical simulation using models that must be well-validated experimentally—as well as predictive algorithms that must undergo thorough validation and also offer robustness, explainability and uncertainty quantification. Thus, AI does not replace traditional measurement instruments and methods, but serves as a powerful tool for enhancing their performance, automation, and reliability. This workshop aims to share various approaches to using AI in the field of nuclear measurements.

Details to be announced soon.