Samuli Eldfors

Research Scientist @Massachusetts Eye and Ear

Cambridge, MA, US
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WORK HISTORY

Jul 2024 — Present

Research Scientist @Massachusetts Eye and Ear

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Boston, MA, US

Analyzed plasma cfDNA samples across diagnostic, longitudinal MRD, and pre-diagnostic cohorts (HPV-associated cancers + cancer-negative controls) on an HPC cluster.• Built and maintained an end-to-end, UMI-aware bioinformatics pipeline (QC, ctDNA quantification, SNV/indel calling, structural variant detection) enabling ultra-sensitive liquid biopsy and MRD monitoring.• Implemented a patient-linked SQL results/QC database for samples, enabling rapid cohort queries, reproducible reporting, and streamlined downstream analysis.• Developed a method to detect and map viral integration breakpoints and associated host structural variation from targeted-capture plasma cfDNA sequencing; validated key events with orthogonal long-read sequencing in matched tumor tissue.• Improved low-VAF signal detection by integrating duplex UMI error correction, index-hopping mitigation, background modeling, and data-driven QC thresholds—reducing false positives and improving robustness at the detection limit.• Built and evaluated ctDNA classification models for cancer vs control; optimized decision thresholds and reported cohort-level performance.

EDUCATION

N/A

University of Helsinki

M.Sc., Biochemistry

N/A

University of Helsinki

PhD, Genetics

2005 — 2007

Aalto University

Minor in Strategy and International Business Management, Industrial engineering and management

ABOUT SAMULI ELDFORS

Computational biologist and cancer researcher with 15+ years in bioinformatics and cancer genomics, focused on liquid biopsy, multi-omics integration, and biomarker discovery for precision oncology. I build robust NGS pipelines and analyze complex datasets in Python and R, with 36+ peer-reviewed publications in hematology and oncology.Specialities:Oncology Data ScienceTranslational BioinformaticsClinical Development AnalyticsLiquid Biopsy AnalyticsReal-World Data (RWD)Real-World Evidence (RWE)Clinical PhenotypingBiomarker Discovery and ValidationGenomics and Molecular OncologyNGS Data Processing and QCMulti-Omics Data AnalysisHigh-Dimensional Data AnalysisStatistical Modeling and BiostatisticsApplied Machine Learning in BiomedicineAI and Generative AI (Applied)Clinical Trial and Observational Data AnalysisDecision Support for Drug DevelopmentCross-Functional R&D Collaboration

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