Topic: energy requirements

This meeting examines how brain-inspired hardware could reduce AI’s growing energy requirements. Researchers connect materials and memory devices with circuits, systems and applications, including sparse computation and compute-in-memory architectures that reduce data movement. Two discussion days address fundamental advances and challenges; the final day considers translation and wider impacts. Programme participants include Steve Furber, Judith Driscoll and Tony Kenyon. The meeting takes place at The Royal Society, 6–9 Carlton House Terrace, London SW1Y 5AG, or online, on 23–25 November 202

Conduct life-cycle and technoeconomic analyses of industrial technologies, including recovery of critical minerals from electronic waste. Use primary equipment and industrial data to quantify costs, energy requirements and environmental performance, and communicate findings through publications and project reports. 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.