Aurél
Prósz
I build frontier AI systems for the life sciences, amplifying researchers and helping humanity confront its deadliest diseases.
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PrószPhD
I build and deploy LLMs that solve scientific problems, backed by 8+ years of industry experience.
I started in physics and biosensing, moved into computational cancer research, and now work on software that lets scientists run complex analyses directly.
My research covers DNA-repair deficiencies, mutational signatures, epigenetics and multimodal cancer data. At PharosBio, I apply that background to scientific agents and research tooling.
At PharosBio, I lead a team of four AI researchers and engineers. I also deploy and host frontier open-weight models, including GLM-5.2, on Gefion, Denmark's AI supercomputer. This gives me hands-on experience running large language models in production.
Technical lead for Hydra, a platform that plans, runs, and checks scientific analyses across approximately 100 databases and 200+ codified skills. As co-founder, successfully raised $150K+ in equity funding.
Visit PharosBioComputational work in cancer genomics, DNA-repair deficiency, multimodal biomarkers, and language-model reasoning in biology, supported by $2M+ in grant funding.
View publicationsStudied genomic aberration profiles and the mechanisms behind cancer-associated DNA-repair pathway deficiencies, including an external stay at Dana-Farber Cancer Institute.
View profileAs one of Turbine.AI’s first employees, I helped the simulated-cell AI company grow from an early startup into a scaled organization through more than four funding rounds and a valuation above $150M. In the Data Team, I developed statistical methods for evaluating in vitro and in silico experiments and built machine-learning workflows in R and Python, including clustering, principal component analysis, logistic regression, and data visualization.
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Chimera SolutionsSelected
projects
Click a project to see what it does, the scale of the work, and the underlying paper or repository.
All repositoriesHydra
A scientific analysis platform that plans work, runs tools and databases, and checks its own results.
- ~100 scientific databases
- 200+ codified skills
- analysis from a single prompt
My research in AI and life sciences
Unconstrained generation of synthetic antibody–antigen structures to guide machine learning methodology for antibody specificity prediction
Nature Computational Science2026Zero-shot biological reasoning with open-weights large language models reproduces CRISPR screen based prediction of synthetic lethal interactions
bioRxiv2024Biologically informed deep learning for explainable epigenetic clocks
Scientific Reports2023Nucleotide excision repair deficiency is a targetable therapeutic vulnerability in clear cell renal cell carcinoma
Scientific ReportsAchievements
Three hackathon wins and more than five conference talks and posters across Europe and the USA.
Hackathon wins
Conference talks
and posters
View event Most recent conference talk · Boston, USA
AI Health Frontiers 2026
Check out my latest writing about technology and AI
Following the signal through the noise in AI, from frontier models to the systems changing how research gets done.

The new data science question: What should AI be allowed to change?
When every dataset can become a hundred analyses, control matters as much as creativity.
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Vibe Coding with AI in Minutes
How to build simple apps with AI to make your work easier, or just because why not?
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From biological sequences to scientific discovery
Introducing the artificial intelligence models that will drive scientific discovery in the future
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