Topic: scientific research

Build experimental biology programmes that help AI systems perform useful scientific research. Design molecular biology and biochemistry experiments, develop functional high-throughput screens and collaborate with computational researchers on AI-agent planning and evaluation. The role connects laboratory evidence with model capabilities. The advertised annual salary is USD 300,000–320,000. Anthropic’s hybrid policy requires at least 25% office attendance, with some roles requiring more.

Dimitris Papailiopoulos of Microsoft Research and the University of Wisconsin discusses how coding agents change scientific research. The conversation covers small arithmetic transformers, symbolic mathematical reasoning, interacting agents, and the role of human judgment and verification. It also examines diversity in machine-generated ideas, benchmark and harness overfitting, persistent agent errors, continual learning, world models, and where information theory helps explain AI. Hosted by Ravid Shwartz Ziv and Allen Roush; the full conversation is available on the publisher's YouTube channe

This seminar, hosted by the LIBRE hub project, will provide an in-depth introduction to the Global Open Science Hardware (GOSH) movement. Since its inception, GOSH has been instrumental in advancing open-source hardware within scientific research, fostering a diverse and active community. The seminar will cover the history of GOSH, its current initiatives, and future opportunities, with a particular focus on the contributions and activities of the Latin American branch. This session aims to inform researchers, educators, and policy-makers about the significance and impact of GOSH in promoting

There are many mysteries in the universe. One of the most significant, often considered the final frontier in science, is understanding how our subjective experience, or consciousness, emerges from the collective action of neurons in biological systems. While substantial progress has been made over the past decades, a unified and widely accepted explanation of the neural mechanisms underpinning consciousness remains elusive. The field is rife with theories that frequently provide contradictory explanations of the phenomenon. To accelerate progress, we have adopted a new model of science: adver

It is now widely accepted that openness and transparency are keys to improving the reproducibility of scientific research, but many challenges remain to adoption of these practices. I will discuss the growth of an ecosystem for open science within the field of neuroimaging, focusing on platforms for open data sharing and open source tools for reproducible data analysis. I will also discuss the role of the Brain Imaging Data Structure (BIDS), a community standard for data organization, in enabling this open science ecosystem, and will outline the scientific impacts of these resources.

As questions of race and justice have risen to the fore across the sciences, the ALBA Network has invited Dr Shakir Mohamed (Senior Research Scientist at DeepMind, UK) to provide a keynote speech on Artificial Intelligence and racism, and the implications for scientific research, that will be followed by a discussion chaired by Dr Konrad Kording (Department of Neuroscience at University of Pennsylvania, US - neuromatch co-founder)