There's good probability that within next 10 years some/most of that work "judging results" will be automated through machine learning.
Re:The Hallmarks of Aging (2013)
by throwawaymath on Friday January 04, 2019 @05:40PM
(#18828414)
Why do you say that?
Well, I can speak to this since I work for a company that does this. The improvement in microscope image analysis by computers in the past 5 years has been amazing. If the trajectory continues, I would say that 25% of image analysis will be automated using DNNs and other machine learning techniques.
Areas where it won't work: any time you have new image data that doesn't resemble what the networks were trained on. In fact, most people in the field recommend training on and running inference on a single microscope and if you change scopes, you have to retrain your model! Obviously data augmentation has a lot to contribute there but there a ton of challenges.
I've actually proposed building a warehouse-scale microscopy facility within a couple miles of amazon or google data center with full realtime reinforcement learning loop. If you have hundreds of near-identical scopes collecting the same data, you can train over the variation.
Re:The Hallmarks of Aging (2013)
by semi-extrinsic on Friday January 04, 2019 @05:47PM
(#18828462)
Plus you get lab snacks if you go this route. If you order both from the US and European warehouses, you even get a wider variety of snacks.
you shouldn't expect, with your academic pedigree and work experience, to be able to pick up enough biology to be truly useful for deep discovery. You can help out writing code, but don't expect to be able to design, run, and analyze the results of an experiment. In biology, it takes decades to be able to judge the results (very different from computer science and machine learning).