This thread may get closed because you have shown relatively little effort.
But before it does, I think it's important that you identify part of bioinformatics, or part of the R/bioconductor ecosystem that is important/interesting to you. It will be extremely hard for you to write an interesting talk on something unless that something sparks an interest for you.
Could you expand upon the purpose of the talk and give an outline of what the expected contents of the talks should be:
are you to present a data-analysis of your own,
are you to summarise a data-analysis method,
are you to able to discuss the software design / architecture underpinning this stuff,
are you able to discuss the social aspects or the publication aspects of coding and releasing packages.
You should take a step back and think about what the challenges in bioinformatics are in 2020, and (based on your question) how does R solve those problems. For me the biggest challenge is reproducibility.
How to contribute to Bioconductor
seems most of them are dimension reducing tools / classifiers to me. You can pick up classifiers such Random forest, CART, SVMs, Lasso regression etc.