Medicinal Chemistry workshops

A five-day research workshop combines molecular simulations and AI-assisted drug discovery with practical hacking sessions and direct mentoring. Training covers enhanced sampling, QM/MM simulation and free-energy calculations, with discussion of current computational research workflows. The meeting brings together forty participants spanning master’s students, doctoral researchers, postdoctoral researchers and faculty, alongside invited experts from Europe, the United States and South America. Activities take place at Universidad de los Andes and Universidad Nacional de Colombia in Bogotá. Pre-registration is first come, first served through 20 October; the local organizer lists a COP 95,000 fee including four lunches and separate travel/accommodation scholarship support.

Apply machine learning throughout drug discovery, from biological target identification to molecular screening. The workshop explains model design, training, evaluation and prediction interpretation, then develops deep-learning and graph-neural-network methods in PyTorch. Practical work turns molecular and omics data into model inputs, implements a graph model from a scientific paper, and examines disease classification and target discovery. The final day builds pipelines from research databases and introduces language-model fine-tuning using biological data. Live online, 30 November–3 December, 14:00–19:00 Europe/Berlin (CET). Fee €480. Aimed at MSc/PhD students and early-career scientists, with basic Python, molecular biology, chemistry and data-analysis knowledge. Previous machine-learning experience is unnecessary.