PhD student in genetics wondering about next professional steps
Hey there!
I recently transitioned from an MSc to a PhD in the same lab, focusing on human telomere epigenetics. I’m currently the only student in a traditionally wet-lab environment, which has given me the unique (and slightly terrifying) opportunity to act as our computational lead.
Over the last two years, I’ve established our lab's first bioinformatics pipelines for WGBS and telomere Nanopore-seq (specifically, looking at telomere and subtelomere length, sequence and methylation). I’ve been heavily using AI (Claude/Gemini) for help with coding and pipeline architecture (R, bash, learning how to use my university's servers, etc).
I’m interested in genetics and gene therapy, but also in bioinformatics, and potentially interweaving the two. I want to ensure my PhD years aren't spent just validating my CRISPR colonies and growing cells- but are actually helping me build myself as someone fluent in both the wet-lab and dry-lab/bioinformatics/data technologies that, from what I can tell, are in demand in industry. I think that people at my level, who know how to leverage AI/LLMs, but don't really understand the nitty gritty of it, will not have much of a chance in the data world.
So, some questions for folks in genetics, genomics, bioinformatics:
- Is "wet/dry lab hybrid" a strong career path? Or are we moving toward hyper-specialization in certain areas?
- What are the skills you would put an emphasis on learning as a solo student, self-taught kinda-sorta-bioinformatician, and how would you go about learning them?
- What company names should I be on the lookout for in these areas?
Thank you for reading!