A large part of Eva's scientific activities has been devoted to the molecular basis of drought stress responses in diverse crop and forestry species. She was involved in projects where RADseq, classical SNP genotyping, and comparative transcriptomics were used for finding key genes and pathways driving stress tolerance. The fact that high amount of data is beeing generated and its proper analysis is a challanging task, she decided to enroll in a Master's program studying Bioinformatics. In her Master Thesis supervised by Moi, she will use deep learning framework to flexibly design and test multiple Neural Network models that can better infer genetic vulnerabilities of populations to a climate impact.