I'm in the building sciences. The biggest unanswered question we come up against almost daily is "what the fuck was the last guy thinking?".
And we avoid, daily, admitting we were the last guy somewhere else.
Trying to prevent bacteria from developing antimicrobial resistance. At these rates in 30 years antimicrobial resistant bacteria are projected to kill more people than cancer.
I'm only a professional scientist in the loosest sense of the term but for years we've tried to figure out why Joe can't leave the break room to fart and who the fuck does he think he is?
How to get supervisors, superintendents, school boards, and even politicians to let teachers teach. It’s understood that overtesting reduces learning. It’s understood that rigid curriculums don’t work, and you really should be tailoring lessons to the capabilities of the class. All
kinds of educational philosophy is understood well and in depth… but being permitted to apply any of it?
Probably not the most complex, but in programming, the salesman problem: intuitive for humans, really tough for programming. It highlights how sophisticated our brains are with certain tasks, and what we take for granted.
I feel inappropriate near all the very universal questions here, but as a paleontologist specialised in some reptilian groups, the question would probably be "where the fuck do turtles come from?!"
The thing is that fossil evidence points to different answers when compared to genetic evidence, and thez separated long enough from other extant groups that we keep on having new "definitive" answers every year
When I was a graduate student, I studied magnetism in massive stars. Lower mass stars (like our sun) demonstrate convection in their outermost layers, which creates turbulent magnetic fields. About 1 in 10 higher mass stars (more than ~8x the mass of the sun) host magnetic fields that are strong and very stable. These stars do not have convection in their outer layers (and thus can’t generate magnetic fields in the same fashion as the sun), and it is thought that these fields are formed very early in the star’s life. Despite much effort, we haven’t really figured out how that happens.
As someone on the outskirts of Data Science, probably something along the lines of "Just what the fuck does my customer actually need?"
You can't throw buzzwords and a poorly labeled spreadsheet at me and expect me to go deep diving into a trashheap of data to magically pull a reasonable answer. "Average" has no meaning if you don't give me anything to average over. I can't tell you what nobody has ever recorded anywhere, because we don't have any telepathic interfaces (and probably would get in trouble with the worker's council if we tried to get one).
I'm sure there are many interesting questions to be debated in this field, but on the practical side, humans remain the greatest mystery.
My brother works in molecular biology; he tells me the field’s understanding of peptides have only just begun and it’s only through machine learning that they are now starting to make progress. 99% seem to be post-translational garbage, the other 1% is likely to be the basis of a revolution of treatment options.
How to accurately estimate signal crosstalk and power delivery performance without FEM/MoM simulators.
For people and companies that can't afford 25k-300k per year in licence and compute costs, there is yet to be a good standard way to estimate EM performance. Not to mention dedicated simulation machines needed.
That's why these companies can charge so damn much. The systems are so complex that making a ton of assumptions to pump out some things by hand or with bulk circuit simulators often doesn't even get close to real world performance.
If someone figured out an accurate method without those simulations, the industry could also save a shit ton of compute power and time.