The practical course focuses on the evolution of study methods in population genomics, driven by the rapid growth of DNA sequence production and sharing. Participants will learn fundamental concepts and advanced approaches to reconstruct the demographic history of populations and infer natural selection, using both classic techniques and machine learning-based methods. Essential and advanced programming skills will also be developed, with a special focus on machine learning.

The course includes keynote lectures on major achievements and future perspectives in population genomics, alongside hands-on activities led by experienced and inspiring speakers. Participants will gain the confidence to run analyses independently.

The course is aimed at evolutionary biologists with basic bioinformatics skills; a good knowledge of R is required, and Python knowledge is a plus. PhD students and postdoctoral researchers will benefit the most from this course, but applications will be evaluated based on individual context.

EMBO Courses and Workshops are selected for their scientific excellence, networking opportunities, and gender diversity among speakers (at least 40% of speakers must be from underrepresented genders). Additionally, organizers are encouraged to implement measures to make the event more environmentally sustainable.