Part I: if all(academia): continue
I spent most of my life breathing academia.
I did my BSc, MSc, and two PhDs across Germany and the US. Research shaped how I think, how I speak, how I measure time. Deadlines, papers, grants, citations – all part of a rhythm I once thought was the rhythm of intellectual life.
After a long winter abroad, I returned to Brazil – first to teach at the same university where my academic path began, and later to join the Oswaldo Cruz Foundation, invited to work on one of the largest precision medicine initiatives in the country. Brazil has one of the world’s largest & most comprehensive free public healthcare systems, and I deeply believe in that model. Open science, open access, open collaboration – those values were never abstract to me.
Then life interrupted.
Part II: driver.wait()
A serious accident left me unable to move or work for a long period. I stepped away from my position with a difficult letter – one of those moments where professionalism and humanity blur completely. There were tears. There was gratitude. And then there was silence.
With my body paused, my mind wasn’t. Learning was the only thing I could still do. So I started looking outward – really outward – in a way I hadn’t had time to before.
What I found surprised me.
Academia is absolutely fundamental. There is no modern AI, no genomics revolution, no computational biology without decades of academic work. That hasn’t changed. What has changed is where some of the most daring experimentation now happens.
For me, “new trends” always meant mathematics/science: variational methods, stochastic optimisation, KL divergence, ELBO, reparameterization tricks – the quiet machinery behind learning systems. Or Any-seq, a novel sequencing method combining gene expression, architecture and function. But outside academia, I suddenly saw something else layered on top of that: tools that fix your code as you write, systems that assume iteration and failure as normal, environments designed to reduce friction instead of rewarding endurance.
I wasn’t ignorant because I lacked curiosity. I was ignorant because academic time is brutally scarce. When survival depends on output metrics, there is little space to look out the window.
Meanwhile, industry quietly absorbed a lesson academia once owned: discovery requires room to fail. By operationalising failure – sharing it, testing it, democratising it – industry started producing research of astonishing quality. Papers like Attention Is All You Need or breakthroughs like AlphaFold weren’t accidents; they emerged from cultures where experimentation was allowed to breathe.
This didn’t diminish academia in my eyes. It reframed it.
Part III: from __future__ import annotations
I realised the question wasn’t academia versus industry. It was whether our systems still align with the values that made discovery possible in the first place.
So I decided to transition.
Not because I stopped believing in research – quite the opposite. I still dream of ambitious endeavours, like chromatin-informed therapies and biology that genuinely changes lives. I just came to believe that the walls separating “industry” and “academia” are more historical than necessary.
Will this transition be easy? Probably not. Will my academic CV fit cleanly into industry checkboxes? Time will tell.
But this isn’t about me, or about choosing sides. It’s a quiet call for a different mindset – one where academia and industry learn from each other, where failure regains its dignity, and where discovery belongs to anyone willing to look carefully enough.
The world is bigger than we think – sometimes we just need the pause to notice it.
