Learning must be exascale ... computing power is AFFORDABLE; this means that participation in something like computational chemistry has been immensely democratized ... moreover, there are much better databases of important data, pre-print archives and repositories models, data and papers with code ... this means that there are now phenomenal opportunities to learn from other people working in the field
Sharing research data needs to go beyond the simple publication of a research paper. For this reason, allowing the sharing of full data and metadata compliant with the FAIR requirements is an essential cornerstone of data stewardship.
Learning must be exascale ... computing power is AFFORDABLE; this means that participation in something like computational chemistry has been immensely democratized ... moreover, there are much better databases of important data, pre-print archives and repositories models, data and papers with code ... this means that there are now phenomenal opportunities to learn from other people working in the field
Stay abreast of the current literature in topics like "density functional theory" ... and participate in current online schools on topics like "Advanced Materials and Molecular Modelling with Quantum ESPRESSO.
Sharing research data needs to go beyond the simple publication of a research paper. For this reason, allowing the sharing of full data and metadata compliant with the FAIR requirements is an essential cornerstone of data stewardship.
Learn to use Git and the GitLab workflow