Summary
Nicolas Freitas is a computational scientist and PhD-trained systems biologist based in Cambridge, MA, who builds machine-learning driven platforms to model disease progression at single-cell resolution. With a decade of experience spanning Harvard Medical School research fellowships and industry work at Etiome, he designs core computational tools that translate multimodal single-cell, immune-profiling, and proteomic data into interpretable models for target discovery and biomarker validation. His expertise blends probabilistic programming, deep learning, causal inference, and advanced statistical modeling with domain knowledge in immunology, hematology, and cancer, enabling more biologically faithful and clinically actionable predictions. Beyond tooling, he shapes platform strategy to expand into new therapeutic areas and routinely integrates BCR/TCR, CITE-seq, and mass-spec data to enhance biological interpretability. An early career researcher with both academic rigor and product-minded execution, he often bridges hypothesis-driven science and deployable computational workflows.
10 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Computational Biology, 3.89/4.00 (summa cum laude), Bachelor of Science - BS, Computational Biology, 3.89/4.00 (summa cum laude) at Minerva University
Doctor of Philosophy - PhD, Systems Biology, Doctor of Philosophy - PhD, Systems Biology at Harvard University
Baccalaureate with a Mention in Biological and Health Sciences, Baccalaureate with a Mention in Biological and Health Sciences at Colegio Nacional de Buenos Aires
Spanish, English, Portuguese, French, Catalan, German, American Sign Language