Principal Scientist, Product Sciences (Computational Biology)

Position SummaryThe Principal Scientist, Product Sciences (Computational Biology) will establish and lead the computational biology strategy for Oryon’s autologous iPSC-derived dopaminergic neuron therapy. Reporting to the Chief Technical Officer, this individual will use genomic, transcriptomic, and other high-dimensional biological data to deepen our understanding of the product, its variability, and the attributes that matter most for successful development.This is a highly cross-functional scientific role at the intersection of product characterization, stem cell biology, genomics, and CMC. The scientist will build analytical frameworks that connect starting material, cell state, manufacturing history, and product characteristics, and will help translate those data into actionable decisions across product and process development.The work will include genomic and transcriptomic characterization of patient-derived iPSC lines, manufacturing intermediates, and drug product, using approaches such as next-generation sequencing, single-cell analysis, and integrative computational biology. Just as importantly, this individual will help determine which questions should be asked of the data and which measurements are meaningful, rather than simply executing predefined analyses. Candidates from both academic and industry backgrounds are encouraged to apply.Key ResponsibilitiesEstablish and lead Oryon’s computational biology and multi-omic product characterization strategyUse genomic, transcriptomic, and other high-dimensional datasets to define and understand product quality, heterogeneity, and biological stateDevelop computational approaches for evaluating genomic integrity and interpreting genomic findings in the context of patient-derived iPSC manufacturingCharacterize cellular composition, identity, state, and variability across starting material, manufacturing intermediates, and drug productIntegrate orthogonal biological datasets to identify product attributes and signatures that may inform developmentConnect molecular characterization with process and analytical data to understand sources and consequences of product variabilityDevelop quantitative approaches for comparing products across patients, manufacturing runs, process changes, and stages of developmentPartner with Product Sciences, Analytical Development, and Process Development to translate computational findings into experimentally testable hypotheses and development decisionsEstablish reproducible, version-controlled computational workflows and data standards appropriate for a regulated development environmentGuide the selection and application of emerging genomic, single-cell, spatial, and computational technologies where they can materially improve product understandingSelect and oversee external sequencing, bioinformatics, and computational partners as neededContribute computational and genomic expertise to comparability strategies, technical reports, regulatory interactions, and regulatory submissionsServe as a scientific leader across Oryon for computational biology, genomic characterization, and quantitative interpretation of complex biological dataQualificationsRequiredPhD in computational biology, bioinformatics, genomics, systems biology, or a related quantitative biological discipline.5+ years of relevant postdoctoral, academic, biotechnology, or pharmaceutical experience.Experience working with human pluripotent stem cells, differentiated human cells, primary human samples, or similarly complex biological systems.Strong command of reproducible computational practices, including version control, documented pipelines, and quantitative quality control.Ability to communicate complex computational findings, assumptions, and limitations clearly to experimental scientists and cross-functional teams.Deep hands-on experience analyzing human genomic or transcriptomic data, with expertise in at least three of the following:Whole-genome or exome sequencingCopy-number and structural-variant analysisSomatic variant analysis and interpretationSingle-cell transcriptomicsBulk RNA sequencingEpigenomic analysisStatistical modeling or machine learning for biological dataMulti-omic data integrationData engineering for large biological datasetsPreferredExperience studying genomic stability or acquired genomic variation in cultured human cellsExperience with iPSC biology, stem cell differentiation, or regenerative medicineExperience analyzing neural single-cell datasets, developmental trajectories, or cell-state transitionsExperience operating in a regulated, clinical genomics, biotechnology, or pharmaceutical environment