Topic: statistical methods

Infer evolutionary relationships and divergence times from multilocus genomic data while accounting for sources of misleading phylogenetic signal. The workshop examines orthologue selection, sequence-evolution models and discordance caused by incomplete lineage sorting and introgression. Lectures and hands-on exercises develop time-calibrated phylogenies and compare the assumptions of alternative inference methods. Analyses run in a prepared cloud environment so participants can concentrate on statistical methods, model choices and interpretation. Live online, 30 November–4 December, 12:00–18

Develop statistical methods that integrate eBird observations with passive acoustic monitoring to improve estimates of bird populations, distribution and change. Work with the Cornell Lab of Ornithology on uncertainty, detection bias and ecological data integration. Two years of funding support consecutive annual appointments, with possible extensions. The Ithaca role offers a hybrid schedule. Submit a cover letter, CV and three referee contacts; review starts 5 October and continues until a suitable candidate is identified.

This NIH BRAIN Initiative funding opportunity supports new or substantially advanced theories, mechanistic or predictive models, and computational or statistical methods that improve quantitative understanding of brain function across scales. Tools must address complex neural and behavioral data and be made broadly available to the neuroscience research community.