Study methods in population genomics have been profoundly reshaped in the last few years, fostered by the rapid growth of DNA sequence production and sharing. This unprecedented opportunity has led to major steps forward in the field and calls for new approaches and computational skills to become routine in evolutionary genomics laboratories.

Participants will learn fundamental concepts and advanced approaches to reconstruct the demographic history of populations and infer natural selection, using both classic and machine learning-based techniques. Participants will also learn the essential and advanced programming skills required to run the analyses related to the concept presented, with a special focus on machine learning. Keynote lectures focused on major achievements and future perspectives of population genomics will complement the training. Lectures and practicals are delivered by experienced, outstanding and inspiring speakers. We expect participants to become fully confident in running analyses on their own after attending the course.

This EMBO Practical Course aims at evolutionary biologists who already have basic bioinformatics skills. Good knowledge of R is a pre-requisite and knowledge of Python is a plus. Ph.D. students and Postdoc researchers will benefit the most from this course, but applications from all candidates will be evaluated in their context.

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