Scientist, Computational Biology

Role: Computational biologist developing and applying advanced computational methods to analyze multi-omics data from minimally invasive biospecimens, supporting early-stage biotech platform development for disease detection. Responsibilities: create scalable pipelines for proteomics, transcriptomics, and proprietary assay data; integrate datasets to identify disease biomarkers; design statistical and machine learning models to enhance assay sensitivity and interpretability; collaborate with biologists and engineers to design experiments, validate hypotheses, and develop analytical tools; ensure reproducibility and documentation; communicate findings to cross-functional teams. Requirements: PhD in computational biology, bioinformatics, systems biology, or related field; 2-4 years industry experience; expertise in NGS, mass spectrometry data analysis, and multi-omics, using R or Python; knowledge of statistical inference and machine learning techniques; experience with mass spectrometry proteomics is strongly preferred; ability to manage multiple projects independently and collaboratively; strong communication skills. HighValue: early-stage biotech, liquid biopsy technologies, multi-omics analysis, biomarker discovery, disease biology, foundational platform development. WorkSetup: not specified, likely hybrid or flexible given early-stage nature.