Topic: energy

This fellowship connects research on climate, energy and environmental issues with policy and public impact. Fellows undertake a mentored research project and an impact-focused capstone while joining interdisciplinary training, retreats and peer-support activities. The programme develops skills in policy translation, public communication, community engagement and research leadership. It provides salary and benefits plus a $6,000 research-support stipend. Core programme activities last one year, with possible extension if funds permit. Applicants use the UC President’s Postdoctoral Fellowship a

This episode examines vanadium compounds as potential medicines and the obstacles separating promising studies from practical treatments. It then turns to the environmental footprint of research laboratories, considering changes in water use, plastics, energy, solvents and other materials. The discussion connects medicinal chemistry with practical questions about making laboratory work more sustainable.

Maximilian Kasy examines the human choices and ownership structures shaping artificial intelligence. After introducing how AI works, he focuses on who determines its objectives and controls the resources needed to build it: data, computing capacity, expertise and energy. The lecture argues that these decisions, rather than autonomous technological inevitability, influence the distribution of AI’s benefits and harms in an already unequal society. It presents a framework for understanding AI capabilities and considers democratic control of objectives and public oversight as responses to those c

Cognitive effort has long been an important explanatory factor in the study of human behavior in health and disease. Yet, the biophysical nature of cognitive effort remains far from understood. In this talk, I will offer a network perspective on cognitive effort. I will begin by canvassing a recent perspective that casts cognitive effort in the framework of network control theory, developed and frequently used in systems engineering. The theory describes how much energy is required to move the brain from one activity state to another, when activity is constrained to pass along physical pathway