Software changed the way humans live, and machine learning is on the verge of doing it again. We started Proscia to use this power to perfect cancer diagnosis by changing the way the world practices pathology.
Our team pushes the limits of medicine and technology, solving problems the world has never solved before. We build software used by thousands of pathologists, proud to know our work is improving outcomes for patients around the globe.
That’s why we’re looking for curious thinkers. Big dreamers. Developers, evangelists, pathologists, and scientists. Exceptional talent to help us shape the future of digital pathology and revolutionize how cancer is fought.
We’re currently hiring for:
We’re always looking for promising talent and new ideas. If you’d like to inquire about an opportunity that’s not listed here, contact us.
A culture built on ideals
Proscia is a workplace driven by shared values. These are the principles that keep us moving forward.
DISRESPECT THE STATUS QUO
We believe great businesses are about solving problems that matter, in ways the world hasn’t tried. That’s why we think big, beyond the day-to-day grind, even when it goes against convention.
Comfort and greatness rarely co-exist. We come hungry to embrace opportunity, especially at this unique moment in time, when our products and people can transform economies and change the way cancer is diagnosed.
Raise the bar
We care about the things we build. That’s why we work to earn the respect of our community by creating beautiful and compelling experiences.
Win as a team
None of us is as smart as all of us. We believe in sharing both the responsibility of disappointments – and the credit for team success.
We deal with powerful technology in matters of life and death, so it’s our responsibility to practice good science, employ a safe and ethical use of AI, and do business with honesty and integrity.
Julianna Ianni is making a difference
As Senior Research Scientist, Julianna is changing the practice of pathology with powerful artificial intelligence. She and her team are implementing deep learning algorithms that are transforming data to solve real-world problems in medicine.