I'm just midway through a masters in bioinformatics, and am currently applying for jobs at deep learning startups, so I'm fairly familiar with AI and genomics.

A few suggestions: - Have you considered cognitive genomics? This is very relevant to the future of intelligence in the absence of radically superhuman AI. Plomin and Steve Hsu (BGI) are the main relevant researchers in this area. - Have you considered identifying pathogenic sequences? Companies that allow biological sequences to be ordered need to be able to accurately identify pathogenic sequences to reduce probabilities of disasters. Don't know much more about this but it's pretty future-relevant and close to your area, possibly even closer than biosecurity risks at large, which is also a good suggestion by Luke. - If by AI, you're interested in machine learning research, then it would make more sense to start with Numpy (or Matlab if you have it), you can transition easily from R, and then C/C++/CUDA for the lower levels and Caffe or Torch for higher-level programming. Java and Hadoop seem more useful for scaling existing algorithms than for researching AI and AI safety.